This disclosure relates generally to extraction of information
from images, and more particularly relates to identifying empty regions within
labels for placing content thereon using image processing.
Background
[002] Generally, labeling refers to labels and other written, printed, or
graphic matter upon an article or containers, wrappers of the article (such as,
but not limited to, a medical device and an automobile device). Typically,
adding content in labeling (also referred as device labeling) may require
manual effort for finding empty regions. Hence, the device labeling becomes
a time-consuming process with increase in labeling operations. With
automation of the device labeling, addition of new content may overlap with
existing content within the label. As a result, automatically
placed content may unintentionally cover or obscure an important information
on the label, thereby negatively affecting user experience.
[003] Accordingly, there is a need for a method and a system that can
identify empty regions within the labels for accurate insertion of the content
without manual intervention and additional hardware.
SUMMARY
[004] In an embodiment, a method for identifying an empty region in
a label and placing a content thereon is disclosed. The method includes
processing an image of the label to extract at least one label attribute and the
content to retrieve at least one content attribute. The image may have a
predefined ratio relative to the label. The at least one label attribute may
include at least one of dimensions of the label, at least one pre-existing
content on the label, dimensions associated with each of the at least one preexisting content, and location of each of the at last one pre-existing content
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on the label. The at least one content attribute may include a type of the
content, dimensions of the content, a preferred label location associated with
the content. The method further includes determining at least one empty
region within the label, based on the extracted at least one label attribute and
the retrieved at least one content attribute. Each of the at least one empty
region may be configured to accommodate the content. The method further
includes inserting the content into one of the at least one empty region based
on a predefined rule.
[005] In another embodiment, a system for identifying an empty
region in a label and placing a content thereon is disclosed. The system may
include a processor and a memory communicatively coupled to the
processor. The memory may be configured to store processor-executable
instructions. The processor-executable instructions, on execution, cause the
processor to process an image of the label to extract at least one label
attribute and the content to retrieve at least one content attribute. The image
may have a predefined ratio relative to the label. The at least one label
attribute may include at least one of dimensions of the label, at least one preexisting content on the label, dimensions associated with each of the at least
one pre-existing content, and location of each of the at last one pre-existing
content on the label. The at least one content attribute may include a type of
the content, dimensions of the content, a preferred label location associated
with the content. The processor instructions further cause the processor to
determine at least one empty region within the label based on the extracted
at least one label attribute and the retrieved at least one content attribute.
Each of the at least one empty region may be configured to accommodate
the content. The processor instructions further cause the processor to insert
the content into one of the at least one empty region based on a predefined
rule.
[006] It is to be understood that both the foregoing general description
and the following detailed description are exemplary and explanatory only
and are not restrictive of the invention, as claimed.
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BRIEF DESCRIPTION OF THE DRAWINGS
[007] The accompanying drawings, which are incorporated in and
constitute a part of this disclosure, illustrate exemplary embodiments and,
together with the description, serve to explain the disclosed principles.
[008] FIG. 1 is a block diagram that illustrates an environment for an
image processing system for identifying an empty region in a label to place
content thereon, in accordance with an embodiment.
[009] FIG. 2 is a functional block diagram that illustrates an exemplary
image processing system for identifying an empty region in a label to place
content thereon, in accordance with an embodiment.
[010] FIGS. 3A and 3B collectively illustrate an exemplary image of a
label used in device labeling for identifying an empty region in the label and
placing content thereon, in accordance with an embodiment.
[011] FIG. 4 is a flowchart that illustrates an exemplary method for
identifying an empty region within a label to place content thereon, in
accordance with an embodiment.
[012] FIG. 5 is a flowchart that illustrates an exemplary method for
determining at least one empty region within a label to place content thereon,
in accordance with an embodiment.
DETAILED DESCRIPTION
[013] Exemplary embodiments are described with reference to the
accompanying drawings. Wherever convenient, the same reference numbers
are used throughout the drawings to refer to the same or like parts. While
examples and features of disclosed principles are described herein,
modifications, adaptations, and other implementations are possible without
departing from the spirit and scope of the disclosed embodiments. It is
intended that the following detailed description be considered as exemplary
only, with the true scope and spirit being indicated by the following claims.
Additional illustrative embodiments are listed below.
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[014] The following described implementations may be found in the
disclosed system and method for identifying an empty region in a label and
placing a content thereon. The disclosed system may identify the empty
region for inserting the content such that the content does not obscure salient
pre-existing content within the label. The disclosed system may facilitate
automatic labeling, such as, but not limited to, a medical device labeling and
an automobile device labeling. Exemplary aspects of the disclosure provide
a system that can identify the empty regions in an image for a label by using
a relatively simple software algorithm with no additional hardware
requirement. In accordance with an embodiment, a pixel-by-pixel
comparison-based algorithm may be used for identifying one or more empty
regions within the label. Therefore, memory requirement and a computational
complexity of the disclosed system is very less.
[015] The disclosed system may determine empty regions in a digital
document (of a label) automatically which facilitates insertion of content (such
as, texts and icons) in a device labeling process and a comment writing
process without overlapping any pre-existing content. Therefore, the
disclosed system and method may also facilitate content adding process with
complete automation that requires no manual intervention. The disclosed
system also facilitates region specific placement of the content in an image
of the label based on a preferred label location. For example, an icon may be
placed in an empty region adjacent to the preferred label location provided
by a user (a content provider).
[016] The disclosed system may facilitate removal of configuration
steps from a user, removal of a requirement for the additional hardware,
removal of manual errors (like overlapping the content over pre-existing
content) and reliably ensuring that content may be accurately placed within
the label. Also, automatic device labeling may speed up the labeling operation
as compared to the manual device labeling.
[017] FIG. 1 is a block diagram that illustrates an environment 100 for
an image processing system for identifying an empty region in a label to place
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content thereon, in accordance with an embodiment. The
environment 100 includes an image processing system 102, a data store 104
within the image processing system 102, a server 106, an external device
108, and a communication network 110.
[018] The image processing system 102 may be communicatively
coupled to the server 106, and the external device 108, via the
communication network 110. The image processing system 102 may include
an application (not shown in FIG. 1) stored in a memory of the image
processing system 102.
[019] The image processing system 102 may include suitable logic,
circuitry, interfaces, and/or code that may be configured to identify at least
one empty region (hereinafter referred as an empty region) within a label for
inserting content in the empty region of an image of the label. In accordance
with an embodiment, the image may also correspond to a digital document
for the label. The image processing system 102 may be configured to quantify
identified empty regions. For example, the empty regions are quantified in
terms of the dimensions of the content and the type of content that may be
inserted within one of the empty regions. In accordance with an embodiment,
the quantification may be a number of characters of text content in a certain
point size that would fit in the empty region. In accordance with an
embodiment, the image processing system 102 may be configured to process
a plurality of images associated with different labels serially or in parallel to
identify the empty regions within each of the plurality of images for placing
the content.
[020] In accordance with an embodiment, the image processing
system 102 may use the application for application-specific deployment that
includes software and/or logic to identify empty regions in an image of a label.
By way of example, the image processing system 102 may be implemented
as a plurality of distributed cloud-based resources by use of several
technologies that are well known to those skilled in the art. In accordance with
an embodiment, the image processing system 102 may include one or more
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dedicated computers. Other examples of implementation of the image
processing system 102 may include, but are not limited to, a web/cloud
server, an application server, a media server, and a Consumer Electronic
(CE) device.
[021] In accordance with an embodiment, the data store 104 may
store the images received by the image processing system 102 and data
associated with the images for access by users of the image processing
system 102. For example, the data store 104 may store metadata along with
the received images and may be accessed via the communication network
110.
[022] In accordance with an embodiment, the data store 104 may
store data structures for use in image processing of the images, for example,
pixel intensity value index used for identifying the empty region(s) in the
image, and the like. While the example of FIG. 1 includes a single data store
(the data store 104) as part of the image processing system 102, it should be
understood that data store 104 may also be located elsewhere in the
environment 100. For example, a discrete storage device may be coupled
with the image processing system 102, via a local connection or over the
communication network 110.
[023] The server 106 may include suitable logic, circuitry, interfaces,
and/or code that may be configured to store, maintain, and execute one or
more software platforms and programs, such as, one or more databases.
Although in FIG. 1, the image processing system 102 and the server 106 are
shown as two separate entities, this disclosure is not so limited. Accordingly,
in some embodiments, the entire functionality of the server 106 may be
included in the image processing system 102, without a deviation from scope
of the disclosure.
[024] The external device 108 may include suitable logic, circuitry,
interfaces, and/or code that may be configured to transmit images of labels
to the image processing system 102 for processing. The external device 108
may be capable of communicating with the image processing system 102 and
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the server 106 via the communication network 110. The external device 108
and the image processing system 102 are generally disparately located.
[025] In accordance with an embodiment, the external device 108
may also be configured to represent the images of the labels in a format that
is independent of methods that are utilized to capture or create those images.
In accordance with an embodiment, images of the labels may include
combinations of different types of content, such as, but not limited to, a text,
an image, a graphics, a shape, an icon and/or barcodes. In accordance with
an embodiment, the external device 108 may receive documents associated
with the labels. In accordance with an embodiment, the documents may also
include metadata, such as, but not limited to, a preferred location, a forbidden
location, and reference fonts which are required to insert the content within
the label.
[026] In accordance with an embodiment, the external device 108
may also include a digital imaging part, e.g., an image sensor, such as, an
active pixel sensor or a Charge Coupled Device (CCD), for capturing the
images of the label. The image sensor may generate an image for the label
which may be stored in an image buffer in memory of the image processing
system 102 that is accessible by the application. The functionalities of the
external device 108 may be implemented in portable devices, such as a highspeed computing device, and/or non-portable devices, such as an application
server. Examples of the external device 108 may include, but are not limited
to, a computing device, a smart phone, a camera, a mobile device, a laptop,
a personal digital assistant (PDA), a printer and a tablet.
[027] The communication network 110 may include a communication
medium through which the image processing system 102, the server 106,
and the external device 108 may communicate with each other. Examples of
the communication network 110 may include, but are not limited to, the
Internet, a cloud network, a Wireless Fidelity (Wi-Fi) network, a Personal Area
Network (PAN), a Local Area Network (LAN), or a Metropolitan Area Network
(MAN). Various devices in the environment 100 may be configured to connect
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to the communication network 110, in accordance with various wired and
wireless communication protocols. Examples of such wired and wireless
communication protocols may include, but are not limited to, a Transmission
Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol
(UDP), Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Zig
Bee, EDGE, IEEE 802.11, light fidelity(Li-Fi), 802.16, IEEE 802.11s, IEEE
802.11g, multi-hop communication, wireless access point (AP), device to
device communication, cellular communication protocols, and Bluetooth (BT)
communication protocols.
[028] During operation, the image processing system 102 may
receive one or more images for processing from the external device 108. In
accordance with another embodiment, the image processing system 102
may receive the one or more images for processing from other sources, for
example, an internet browser, email, or the like. In accordance with an
embodiment, the image may have a predefined ratio relative to the label. In
accordance with yet another embodiment, the image processing system 102
may also be configured to receive the label from the external device 108.
Accordingly, the image processing system 102 may be configured to
generate the image of the label from the label. The image processing system
102 may be configured to convert the image to a size that is of the predefined
ratio relative to the label.
[029] In accordance with an embodiment, the image processing
system 102 may be further configured to process the image of the label to
extract at least one label attribute and the content to retrieve at least one
content attribute. The content and data associated with the at least one label
attribute and the at least one content attribute may be stored in the data store
104. In accordance with an embodiment, at least one label attribute may
include at least one of dimensions of the label, at least one pre-existing
content on the label, dimensions associated with each of the at least one preexisting content, and location of each of the at last one pre-existing content
on the label. In accordance with an embodiment, the at least one content
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attribute may include a type of the content, dimensions of the content, a
preferred label location associated with the content. In accordance with an
embodiment, the image processing system 102 may be configured to retrieve
the at least one content attribute from the content using an image processing
algorithm.
[030] In accordance with an embodiment, the image processing
system 102 may be further configured to determine at least one empty region
within the label based on the extracted at least one label attribute and the
retrieved at least one content attribute. In accordance with an embodiment,
each of the at least one empty region may be configured to accommodate
the content. In accordance with an embodiment, the at least one empty region
may be represented by a dotted line in the image of the label.
[031] In accordance with an embodiment, the image processing
system 102 may be further configured to insert the content into one of the at
least one empty region based on a predefined rule. An example of the
predefined rule may include that a user (content provider) has already chosen
to place the content in a preferred label location and such preferred label
location may be a part of metadata linked to the content. Accordingly, the
image processing system 102 may check against such predefined rule to
ensure that the content is placed into a suitable empty region. Thereby, the
content may be automatically and preferably inserted in the suitable empty
region of the image.
[032] The predefined rule may also include labeling guidelines from
a regulatory authority for positioning the content within a certain region of the
label, based on the type of the content and an end product for affixing the
label. In accordance with an embodiment, the labeling guidelines may also
obscure certain regions in the label for positioning the content, based on the
type of the content and an end product for affixing the label. Therefore, the
image processing system 102 may automatically and preferably insert the
content in the suitable empty region of the image without overlapping with the
existing content.
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[033] While example embodiments described herein generally relate
to determining empty regions in an image of the label for placing the content
thereon, example embodiments may also be implemented for placing, without
limitation, advertising banners and text advertisements based on
identification of empty regions in web pages.
[034] All the components in the environment 100 may be coupled
directly or indirectly to the communication network 110. The components
described in the environment 100 may be further broken down into more than
one component and/or combined together in any suitable arrangement.
Further, one or more components may be rearranged, changed, added,
and/or removed.
[035] FIG. 2 is a functional block diagram that illustrates an exemplary
image processing system for identifying an empty region in a label to place
content thereon, in accordance with an embodiment. FIG. 2 is explained in
conjunction with elements from FIG. 1.
[036] With reference to FIG. 2, there is shown a functional block
diagram 200 of the image processing system 102. The image processing
system 102 may include a processor 202, a memory 204, an input/output
(I/O) device 206, a network interface 208, a data store 104, a processing
module 210, an empty region determination module 212, and a content
insertion module 214.
[037] The processor 202 may be communicatively coupled to the
memory 204, the I/O device 206, the network interface 208, the datastore
104, the processing module 210, the empty region determination module 212,
and the content insertion module 214. In one or more embodiments, the
image processing system 102 may also include a provision/functionality to
capture an image of a label via one or more external devices, for example,
the external device 108.
[038] Elements and features of the image processing system 102
may be operatively associated with one another, coupled to one another, or
otherwise configured to cooperate with one another as needed to support the
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desired functionality, as described herein. For ease of illustration and clarity,
the various physical, electrical, and logical couplings and interconnections for
the elements and the features are not depicted in FIG. 2. Moreover, it should
be appreciated that embodiments of image processing system 102 will
include other elements, modules, and features that cooperate to support the
desired functionality. For simplicity, FIG. 2 only depicts certain elements that
relate to the techniques described in more detail below.
[039] The processor 202 may include suitable logic, circuitry,
interfaces, and/or code that may be configured to process images of the
labels for device labeling operations and content addition operations. The
processor 202 may be implemented based on a number of processor
technologies, which may be known to one ordinarily skilled in the art.
Examples of implementations of the processor 202 may be a Graphics
Processing Unit (GPU), a Reduced Instruction Set Computing (RISC)
processor, an Application-Specific Integrated Circuit (ASIC) processor, a
Complex Instruction Set Computing (CISC) processor, a microcontroller,
Artificial Intelligence (AI) accelerator chips, a co-processor, a central
processing unit (CPU), and/or a combination thereof. The processor 202 may
be communicatively coupled to, and communicates with, the memory 204.
[040] The memory 204 may include suitable logic, circuitry, and/or
interfaces that may be configured to store instructions executable by the
processor 202. Additionally, the memory 204 may be configured to store
program code of one or more software applications that may incorporate the
program code of the one or more image processing algorithms. The
memory 204 may be configured to store any received data (such as, digital
documents, images of the label) or generated data associated with storing,
maintaining, and executing the image processing system 102 used to identify
empty regions within the label. Examples of implementation of the memory
204 may include, but are not limited to, Random Access Memory (RAM),
Read Only Memory (ROM), Electrically Erasable Programmable Read-Only
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Memory (EEPROM), Hard Disk Drive (HDD), a Solid-State Drive (SSD), a
CPU cache, and/or a Secure Digital (SD) card.
[041] The I/O device 206 may include suitable logic, circuitry, and/or
interfaces that may be configured to act as an I/O interface between a user
(such as, a content provider) and the image processing system 102. The I/O
device 206 may include various input and output devices, which may be
configured to communicate with different operational components of the
image processing system 102. The I/O device 206 may be configured to
communicate data between the image processing system 102 and one or
more of the server 106, and the external device 108.
[042] As described in more detail below, data received by the I/O
device 206 may include, without limitation: images of the label, documents of
the label, metadata of the label and data compatible with the image
processing system 102. Data provided by the I/O device 206 may include,
without limitation, content placement in identified empty regions within the
label, and the like. Examples of the I/O device 206 may include, but are not
limited to, a touch screen, a keyboard, a mouse, a joystick, a microphone, a
printer, and a display screen.
[043] The network interface 208 may include suitable logic, circuitry,
interfaces, and/or code that may be configured to facilitate different
components of the image processing system 102 to communicate with other
devices, such as the server 106, and the external device 108, in the
environment 100, via the communication network 110. The network interface
208 may be configured to implement known technologies to support wired or
wireless communication. Components of the network interface 208 may
include, but are not limited to an antenna, a radio frequency (RF) transceiver,
one or more amplifiers, a tuner, one or more oscillators, a digital signal
processor, a coder-decoder (CODEC) chipset, an identity module, and/or a
local buffer.
[044] The network interface 208 may be configured to communicate
via offline and online wireless communication with networks, such as the
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Internet, an Intranet, and/or a wireless network, such as a cellular telephone
network, a wireless local area network (WLAN), personal area network,
and/or a metropolitan area network (MAN). The wireless communication may
use any of a plurality of communication standards, protocols and
technologies, such as Global System for Mobile Communications (GSM),
Enhanced Data GSM Environment (EDGE), wideband code division multiple
access (W-CDMA), code division multiple access (CDMA), LTE, time division
multiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (such as IEEE
802.11, IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, and/or any other IEEE
802.11 protocol), voice over Internet Protocol (VoIP), Wi-MAX, Internet-ofThings (IoT) technology, Machine-Type-Communication (MTC) technology, a
protocol for email, instant messaging, and/or Short Message Service (SMS).
[045] The data store 106 may include suitable logic, circuitry, and/or
interfaces that may be configured to store program instructions executable by
the processor 202, the processing module 210, the empty region
determination module 212, the content insertion module 214, operating
systems, and/or application-specific information, such as application-specific
databases. The data store 106 may include a computer-readable storage
media for carrying or having computer-executable instructions or data
structures stored thereon. Such computer-readable storage media may
include any available media that may be accessed by a general-purpose or
special-purpose computer, such as the processor 202, the processing
module 210, the empty region determination module 212, and the content
insertion module 214.
[046] By way of example, and not limitation, the data store 104 may
use computer-readable storage media that includes tangible or non-transitory
computer-readable storage media including, but not limited to, Compact Disc
Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk
storage or other magnetic storage devices (e.g., Hard-Disk Drive (HDD)),
flash memory devices (e.g., Solid State Drive (SSD), Secure Digital (SD)
card, other solid state memory devices), or any other storage medium which
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may be used to carry or store particular program code in the form of
computer-executable instructions or data structures and which may be
accessed by a general-purpose or special-purpose computer. Combinations
of the above may also be included within the scope of computer-readable
storage media.
[047] The processing module 210 may include suitable logic,
circuitry, and/or interfaces that may be configured to process the image of the
label to extract one or more label attributes and the content to retrieve one or
more content attributes. The image may have a predefined ratio relative to
the label. In accordance with another embodiment, the processing module
210 may be configured to generate the image of the label from the label. The
processing module 210 may be further configured to convert the image to a
size that is of the predefined ratio relative to the label. The one or more label
attributes extracted by the processing module 210 may include at least one
of dimensions of the label, at least one pre-existing content on the label,
dimensions associated with each of the at least one pre-existing content, and
location of each of the at last one pre-existing content on the label.
[048] In accordance with an embodiment, the processing module 210
may be configured to extract the one or more label attributes that further
includes pixel values associated with each pixel within the image of the label.
In accordance with an embodiment, the processing module 210 may be
configured to process the image of the label that further includes extracting
the pixel values using a pixel-by-pixel comparison-based algorithm. In
accordance with an embodiment, the processing module 210 may be
configured to retrieve one or more content attributes that include a type of the
content, dimensions of the content, a preferred label location associated with
the content. In accordance with an embodiment, the processing module 210
may be configured to process the content to retrieve the one or more content
attributes from a library of images. In accordance with an embodiment, the
library of images may include mapping of a plurality of contents with
associated content attributes.
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[049] The empty region determination module 212 may include
suitable logic, circuitry, and/or interfaces that may be configured to determine
at least one empty region within the label based on the extracted one or more
label attributes and the retrieved one or more content attributes. In
accordance with an embodiment, each of the at least one empty region may
be configured to accommodate the content.
[050] In accordance with an embodiment, the empty region
determination module 212 may be configured to determine an empty region
from the at least one empty region within the label comprises determining a
set of contiguous pixels. In accordance with an embodiment, each pixel in the
set of contiguous pixels may have a predefined pixel value. The predefined
pixel value may correspond to a pixel value for an empty region. The empty
region may include the set of contiguous pixels.
[051] In accordance with an embodiment, the empty region
determination module 212 may be further configured to identify a set of empty
regions in the image of the label. The empty region determination module 212
may be further configured to quantify dimensions of each of the set of empty
regions. The empty region determination module 212 may be further
configured to compare dimensions of each of the set of empty regions with
the dimensions of the content. In accordance with an embodiment, the empty
region determination module 212 may be further configured to identify the at
least one empty region from the set of empty regions. Dimensions of each of
the at least one empty region may be greater than or equal to the dimensions
of the content.
[052] In accordance with an embodiment, the empty region
determination module 212 may be further configured to modify the
dimensions of the content to match the dimensions of a largest empty region
from the at least one empty region, when the dimensions of the content do
not match with the dimensions of each of the at least one empty region.
[053] The content insertion module 214 may include suitable logic,
circuitry, and/or interfaces that may be configured to insert the content into
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one of the at least one empty region based on a predefined rule. In
accordance with an embodiment, the predefined rule may include a first
empty region from the at least one empty region being the preferred label
location associated with the content. The preferred label location may be a
part of metadata linked to the content. In accordance with an embodiment,
the predefined rule may also include selecting a second empty region closest
to the preferred label location associated with the content, when the preferred
label location is unavailable within the label. In accordance with an
embodiment, the predefined rule may further include labeling guidelines from
a regulatory authority for positioning the content within a certain region of the
label, based on the type of the content and an end product for affixing the
label.
[054] In practice, the processing module 210, the empty region
determination module 212, and the content insertion module 214 may be
implemented with (or cooperate with) the at least one processor 202 to
perform at least some of the functions and operations described in more detail
herein. In this regard, the processing module 210, the empty region
determination module 212, and the content insertion module 214 may be
realized as suitably written processing logic, application program code, or the
like.
[055] FIGS. 3A and 3B collectively illustrate an exemplary image of a
label used in device labeling for identifying an empty region in the label and
placing content thereon, in accordance with an embodiment. FIGS. 3A and
3B are explained in conjunction with elements from FIG. 1 and FIG. 2.
[056] With reference to FIG. 3A, there is shown an image 300A of a
label with pre-existing content, such as, barcodes 302 and a thermometer
symbol 304 with temperature readings and icons 306. Some of the preexisting content in the image 300A is not labelled for the sake of brevity.
There is further shown empty regions 308A-308C, dotted lines 310A-310C
associated with the empty regions 308A-308C and star symbols 312A-312C
that signify preferred label locations associated with placement of the content.
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With reference to FIG. 3B that illustrates the image 300B (output image) of
the label with insertion of the content, there is shown placement of the content
314A-314C within different empty regions 308A-308C of the label.
[057] Referring to FIG. 3A, the image processing system 102 may be
configured to receive an image, such as, the image 300A of a label from the
external device 108. In accordance with an embodiment, the image
processing system 102 may receive a document of the label from the external
device and generate the image 300A of the label from the document. In
accordance with another embodiment, the image processing system 102 may
be configured to capture the image 300A of the label. The label may
correspond to, without limitation, a medical device label, or an automobile
label.
[058] In accordance with an embodiment, the image processing
system 102 may be configured to process the image 300A to extract label
attribute(s) of the label associated with the image 300A. Such label attributes
may include dimensions of the label and the image 300A may have a
predefined ratio relative to the label. The pre-existing content of the label as
shown in the image 300A, such as, the barcodes 302, the thermometer
symbol 304 and the icons 306 may also correspond to label attributes.
[059] In accordance with an embodiment, the label attribute may also
include dimensions (size) of the barcodes 302, the thermometer symbol 304
and the icons 306 or font size of pre-existing text if any (not labelled in FIG.
3A) in the image 300A. In accordance with an embodiment, the label attribute
may also include the location of the pre-existing content in the image. The
location of the pre-existing content may be given in terms of geometrical
coordinates, such as x coordinates and y coordinates.
[060] The image processing system 102 may be configured to
receive the content that needs to be placed in an empty region of the image
300A, from the external device 108, via the communication network 110. In
accordance with an embodiment, the image processing system 102 may be
configured to process the content to retrieve one or more content attributes.
Docket No: IIP-HCL-P0072
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In accordance with an embodiment, the content attribute may include a type
of the content. Examples of the type of the content may include at least one
of an icon, a text, an image, an emoji, a logo, a barcode or a shape.
[061] Further, the content attributes may also include dimensions of
the content, such as, a font size for text (content) or a size of an icon (content)
that needs to be added within the label. In accordance with an embodiment,
the content attributes may further include a preferred label location for
insertion of the content within the label. In accordance with an embodiment,
the preferred label location for insertion of the content may be provided to the
image processing system 102 from a content provider, via the communication
network 110.
[062] The preferred label location of the content may be given in
terms of geometrical coordinates, such as x coordinates and y coordinates in
the image 300A of the label. In accordance with an embodiment, the preferred
label location may be a part of metadata linked to the content. In certain
cases, the preferred label location may not be provided by the content
provider for the placement of the content. In such cases, the image
processing system 102 may be configured to assume a starting location of
the image 300A as a preferred label location to determine empty region within
the label, adjacent to such preferred location.
[063] In accordance with an embodiment, the label attribute may
further include pixel values associated with each pixel within the image 300A
of the label. An image, such as the image 300A may correspond to a twodimensional array of values (pixels). Pixels may correspond to picture
element intensity values. The image 300A may correspond to a grayscale
image where the pixels are scalars indicating the intensity of each pixel value.
In accordance with an embodiment, the image processing system 102 may
be configured to separate the background and foreground in the image 300A,
based on the intensity of each pixel value. In accordance with another
embodiment, the image processing system 102 may also be configured to
Docket No: IIP-HCL-P0072
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process a colored image, whose pixels may have values of three-color
channels, viz., red, green, and blue.
[064] The image processing system 102 may be configured to extract
the pixel values from the image 300A of the label, using a pixel-by-pixel
comparison-based algorithm. The image processing system 102 may be
configured to select one or more contiguous image regions (referred as empty
regions) with similar pixel values in the image 300A, using the pixel-by-pixel
comparison-based algorithm. In other words, the image processing system
102 may be configured to determine a set of contiguous pixels in the image
300A to determine one or more empty regions 308 within the image 300A of
the label. Therefore, no additional hardware may be required for device
labeling process. In accordance with an embodiment, each pixel in the set of
contiguous pixels may have a predefined pixel value (or grayscale values). In
accordance with an embodiment, the empty region 308 may include the set
of contiguous pixels.
[065] Bounding boxes to represent the empty regions 308A-308C are
shown for explanation purpose in FIG. 3A only and may not be visible after
placement of the content within the image 300B of the label as will be
explained in description of FIG. 3B. Similarly, dotted lines (310A-310C) are
for illustration purpose that indicate whether the identified empty region
overlaps with the pre-existing content and based on the overlap, new empty
regions may be identified within the label. Furthermore, the image processing
system 102 may be configured to implement the pixel-by-pixel comparisonbased algorithm at an application level for determining empty regions within
the label for placing the content thereon.
[066] In accordance with an embodiment, the image processing
system 102 may be configured to identify a set of empty regions (308A, 308B
and 308C) in the image 300A of the label. The image processing system 102
may be further configured to quantify dimensions of each of the empty regions
300A, 300B and 300C. In accordance with an embodiment, the dimensions
may correspond to height and width of the empty regions (308A-308C). The
Docket No: IIP-HCL-P0072
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image processing system 102 may be further configured to compare the
dimensions of the empty regions (308A-308C) with the dimensions of the
content.
[067] The image processing system 102 may be further configured
to identify at least one empty region from empty regions (308A-308C) for
placement of the content such that dimensions of each of the empty regions
(308A-308C) may be greater than or equal to the dimensions of the content.
For example, the dimensions of the content “The revision details need to be
updated with latest date” are greater than the dimensions of the empty region
308A, but equal to the dimensions of the empty region 308C. Therefore, the
image processing system 102 may be configured to identify the empty region
308C from the empty regions (308A-308C) for placement of the content “The
revision details need to be updated with latest date” within the label.
[068] Further, there may be a predefined rule for labeling guidelines
from a regulatory authority for positioning the content within a certain region
of the label. For example, the content “The revision details need to be
updated with latest date” may be positioned at the bottom right side of the
label, based on the type of the content and an end product (such as, a
pharmaceutical labels) for affixing the label.
[069] Further, based on mismatch of the dimensions of the content
with the dimensions of each of empty regions (308A-308C), the image
processing system 102 may be configured to modify the dimensions of the
content so as to match the dimensions of a largest empty region from the
empty regions (308A-308C). For example, the empty region 300C from the
empty regions (308A-308C) is the preferred label location (shown by the star
symbol 312C) associated with the content “The revision details need to be
updated with latest date” 314C and the empty region 300B from the empty
regions (308A-308C) is the preferred label location (shown by the star symbol
312B) associated with the content of type icon.
[070] For placement of the content “CONTENTS” 314A in the
remaining empty region 308B from the empty regions (308A-308C), the
Docket No: IIP-HCL-P0072
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dimensions of the content are decreased in font size to match the dimensions
of the empty region 308B because the dimensions of the content
“CONTENTS” 314A are greater than the dimensions of the empty region
308B. In certain cases, the image processing system 102 may be configured
to select another empty region closest to a preferred label location associated
with the content, when the preferred label location is unavailable within the
label.
[071] In accordance with an embodiment, the image processing
system 102 may be configured to insert the content 314A into the empty
region 308A, the content 314B into the empty region 308B and the content
314C into the empty region 308C of the image 300B without overlapping with
the pre-existing content, such as, the barcodes 302, the thermometer symbol
304 and the icons 306. In accordance with an embodiment, the empty regions
(such as, the empty regions 308A-308C) may be configured to accommodate
the content.
[072] In accordance with an embodiment, the image processing
system 102 may be configured to convert the image (such as, the image
300B) into a document format and transmit to the external device 108, via the
communication network 110. The image processing system 102 may
facilitate users (such as, content providers) to write comments in the image
of the labels with ease, and receive an output image (such as, the image
300B) with less effort and can be used easily. The writing the comments in
an image or placing the icons within the label becomes easy with automation
of identifying the empty regions in labeling process, such as, a device labeling
and an automobile labeling.
[073] FIG. 4 is a flowchart that illustrates an exemplary method for
identifying an empty region in a label and placing a content thereon, in
accordance with an embodiment. With reference to FIG. 4, there is shown a
flowchart 400. The operations of the exemplary method may be executed by
any computing system, for example, by the image processing system 102 of
Docket No: IIP-HCL-P0072
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FIG. 1. The operations of the flowchart 400 may start at 402 and proceed to
404.
[074] At 402, an image of the label may be processed. In accordance
with an embodiment, the processing module 210 of the image processing
system 102 may be configured to process the image of the label to extract at
least one label attribute and the content to retrieve at least one content
attribute. In accordance with an embodiment, the image may have a
predefined ratio relative to the label. In accordance with an embodiment, the
processing module 210 may be configured to generate the image of the label
from the label and convert the image to a size that is of the predefined ratio
relative to the label.
[075] In accordance with an embodiment, at least one label attribute
may include at least one of dimensions of the label, at least one pre-existing
content on the label, dimensions associated with each of the at least one preexisting content, and location of each of the at last one pre-existing content
on the label. In accordance with an embodiment, the at least one label
attribute further may include pixel values associated with each pixel within the
image of the label. In accordance with an embodiment, the processing
module 210 may be configured to process the image of the label that further
includes extracting the pixel values using a pixel-by-pixel comparison-based
algorithm.
[076] In accordance with an embodiment, the at least one content
attribute may include a type of the content, dimensions of the content, a
preferred label location associated with the content. In accordance with an
embodiment, the at least one content attribute may be retrieved from the
content by the processing module 210 using an image processing algorithm.
In accordance with an embodiment, the at least one content attribute may be
retrieved from a library of images by the processing module 210. In
accordance with an embodiment, the library of images may include mapping
of a plurality of contents with associated content attributes. The type of the
Docket No: IIP-HCL-P0072
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content may include at least one of an icon, a text, an image, an emoji, a logo,
or a shape.
[077] At 404, at least one empty region may be determined within the
label. In accordance with an embodiment, the empty region determination
module 212 may be configured to determine at least one empty region within
the label. Such determination may be based on the extracted at least one
label attribute and the retrieved at least one content attribute. In accordance
with an embodiment, each of the at least one empty region may be configured
to accommodate the content.
[078] In accordance with an embodiment, the empty region
determination module 212 may be configured to determine an empty region
from the at least one empty region within the label that includes determining
a set of contiguous pixels. Each pixel in the set of contiguous pixels may have
a predefined pixel value. The empty region may include the set of contiguous
pixels. The predefined pixel value may correspond to a pixel value for an
empty region.
[079] At 406, the content may be inserted into one of the at least one
empty region based on a predefined rule. In accordance with an embodiment,
the content insertion module 214 of the image processing system 102 may
be configured to insert the content into one of the at least one empty region
based on the predefined rule.
[080] The predefined rule may include a first empty region from the
at least one empty region being the preferred label location associated with
the content. The preferred label location may be a part of metadata linked to
the content. The predefined rule may also include selecting a second empty
region closest to the preferred label location associated with the content,
when the preferred label location is unavailable within the label. The
predefined rule may also include labeling guidelines from a regulatory
authority for positioning the content within a certain region of the label, based
on the type of the content and an end product for affixing the label.
Docket No: IIP-HCL-P0072
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[081] FIG. 5 is a flowchart that illustrates an exemplary method for
determining at least one empty region in a label for placing a content thereon,
in accordance with an embodiment. With reference to FIG. 5, there is shown
a flowchart 500. The operations of the exemplary method may be executed
by any computing system, for example, by the image processing system 102
of FIG. 1. The operations of the flowchart 500 may start at 502 and proceed
to 504.
[082] At 502, a set of empty regions may be identified in the image of
the label. In accordance with an embodiment, the empty region determination
module 212 may be configured to identify a set of empty regions in the image
of the label. For example, a set of empty regions (308A-308C) is identified in
the image 300A of the label as explained in description for FIG.3A-3B.
[083] At 504, dimensions of each of the set of empty regions may be
quantified. In accordance with an embodiment, the empty region
determination module 212 of the image processing system 102 may be
configured to quantify dimensions of each of the set of empty regions.
[084] At 506, dimensions of each of the set of empty regions may be
compared with the dimensions of the content. In accordance with an
embodiment, the empty region determination module 212 of the image
processing system 102 may be configured to compare the dimensions of
each of the set of empty regions with the dimensions of the content.
[085] At 508, the at least one empty region may be identified from the
set of empty regions. In accordance with an embodiment, the empty region
determination module 212 of the image processing system 102 may be
configured to identify the at least one empty region from the set of empty
regions. In accordance with an embodiment, the dimensions of each of the at
least one empty region may be greater than or equal to the dimensions of the
content.
[086] At 510, the dimensions of the content may be modified to match
the dimensions of a largest empty region from the at least one empty region.
In accordance with an embodiment, the empty region determination module
Docket No: IIP-HCL-P0072
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212 of the image processing system 102 may be configured to modify the
dimensions of the content to match the dimensions of a largest empty region
from the at least one empty region, when the dimensions of the content do
not match with the dimensions of each of the at least one empty region.
[087] The disclosed system may determine empty regions in a digital
document (of a label) automatically which facilitates insertion of content (such
as, texts and icons) in a device labeling process and a comment writing
process without overlapping the pre-existing content. Therefore, the
disclosed system and method may also facilitate content adding process with
complete automation that requires no manual intervention. The disclosed
system also facilitates region specific placement of the content in an image
of the label based on a preferred label location. For example, an icon may be
placed in an empty region adjacent to the preferred label location provided
by a user (a content provider).
[088] The disclosed system may facilitate removal of configuration
steps from a user, removal of a requirement for the additional hardware,
removal of manual errors (like overlapping the content over pre-existing
content) and reliably ensuring that content may be accurately placed within
the label. Also, automatic device labeling may speed up the labeling operation
as compared to the manual device labeling.
[089] Furthermore, one or more computer-readable storage media
may be utilized in implementing embodiments consistent with the present
disclosure. A computer-readable storage medium refers to any type of
physical memory on which information or data readable by a processor may
be stored. Thus, a computer-readable storage medium may store instructions
for execution by one or more processors, including instructions for causing
the processor(s) to perform steps or stages consistent with the embodiments
described herein. The term “computer-readable medium” should be
understood to include tangible items and exclude carrier waves and transient
signals, i.e., be non-transitory. Examples include random access memory
(RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard
Docket No: IIP-HCL-P0072
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drives, CD ROMs, DVDs, flash drives, disks, and any other known physical
storage media.
[090] It will be appreciated that, for clarity purposes, the above
description has described embodiments with reference to different functional
units and processors. However, it will be apparent that any suitable
distribution of functionality between different functional units, processors or
domains may be used without detracting from the disclosure. For example,
functionality illustrated to be performed by separate processors or controllers
may be performed by the same processor or controller. Hence, references to
specific functional units are only to be seen as references to suitable means
for providing the described functionality, rather than indicative of a strict
logical or physical structure or organization.
[091] Although the present disclosure has been described in
connection with some embodiments, it is not intended to be limited to the
specific form set forth herein. Rather, the scope of the present disclosure is
limited only by the claims. Additionally, although a feature may appear to be
described in connection with particular embodiments, one skilled in the art
would recognize that various features of the described embodiments may be
combined in accordance with the disclosure.
[092] Furthermore, although individually listed, a plurality of means,
elements or process steps may be implemented by, for example, a single unit
or processor. Additionally, although individual features may be included in
different claims, these may possibly be advantageously combined, and the
inclusion in different claims does not imply that a combination of features is
not feasible and/or advantageous. Also, the inclusion of a feature in one
category of claims does not imply a limitation to this category, but rather the
feature may be equally applicable to other claim categories, as appropriate.

CLAIMS
We claim:
1. A method for identifying an empty region in a label and placing a content
thereon, the method comprising:
processing (402), by an image processing device, an image of the
label to extract at least one label attribute and the content to retrieve at least
one content attribute, wherein the image has a predefined ratio relative to
the label, and
wherein at least one label attribute comprises at least one of
dimensions of the label, at least one pre-existing content on the label,
dimensions associated with each of the at least one pre-existing
content, and location of each of the at last one pre-existing content
on the label, and
wherein the at least one content attribute comprises a type of
the content, dimensions of the content, a preferred label location
associated with the content;
determining (404), by the image processing device, at least one
empty region within the label based on the extracted at least one label
attribute and the retrieved at least one content attribute, and wherein each
of the at least one empty region is configured to accommodate the content;
and
inserting (406), by the image processing device, the content into one
of the at least one empty region based on a predefined rule.
2. The method of claim 1, wherein the predefined rule comprises at least
one of:
a first empty region from the at least one empty region being the
preferred label location associated with the content, wherein the preferred
label location is part of metadata linked to the content;
Docket No: IIP-HCL-P0072
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selecting a second empty region closest to the preferred label
location associated with the content, when the preferred label location is
unavailable within the label; and
labeling guidelines from a regulatory authority for positioning the
content within a certain region of the label, based on the type of the content
and an end product for affixing the label.
.
3. The method of claim 1, wherein the at least one label attribute further
comprises pixel values associated with each pixel within the image of the
label, and
wherein processing (402) the image of the label further comprises
extracting the pixel values using a pixel-by-pixel comparison-based
algorithm, and
wherein determining (404) an empty region from the at least one
empty region within the label comprises determining a set of contiguous
pixels, wherein each pixel in the set of contiguous pixels has a predefined
pixel value, and wherein the empty region comprises the set of contiguous
pixels.
4. The method of claim 3, wherein determining (404) at least one empty
region comprises:
identifying (502) a set of empty regions in the image of the label;
quantifying (504) dimensions of each of the set of empty regions;
comparing (506) dimensions of each of the set of empty regions with the
dimensions of the content;
identifying (508) the at least one empty region from the set of empty
regions, wherein dimensions of each of the at least one empty region is
greater than or equal to the dimensions of the content; and
comprising modifying (510) the dimensions of the content to match the
dimensions of a largest empty region from the at least one empty region,
Docket No: IIP-HCL-P0072
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when the dimensions of the content do not match with the dimensions of
each of the at least one empty region.
5. The method of claim 1, wherein the at least one content attribute is
retrieved from the content using an image processing algorithm, wherein
the at least one content attribute is retrieved from a library of images, and
wherein the library of images comprises mapping of a plurality of contents
with associated content attributes, and wherein the type of the content
comprises at least one of an icon, a text, an image, an emoji, a logo, or a
shape.
6. The method of claim 1, further comprising:
generating the image of the label from the label; and
converting the image to a size that is of the predefined ratio relative
to the label.
7. A system for identifying an empty region in a label and placing a content
thereon, the system comprising:
a processor (202); and
a memory (204) communicatively coupled to the processor (202),
wherein the memory (204) stores processor-executable instructions, which,
on execution, causes the processor to:
process an image of the label to extract at least one label
attribute and the content to retrieve at least one content attribute,
wherein the image has a predefined ratio relative to the label, and
wherein at least one label attribute comprises at least
one of dimensions of the label, at least one pre-existing
content on the label, dimensions associated with each of the
at least one pre-existing content, and location of each of the
at last one pre-existing content on the label, and
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wherein the at least one content attribute comprises a
type of the content, dimensions of the content, a preferred
label location associated with the content;
determine at least one empty region within the label based on
the extracted at least one label attribute and the retrieved at least one
content attribute, and wherein each of the at least one empty region
is configured to accommodate the content; and
insert the content into one of the at least one empty region
based on a predefined rule.
8. The system of claim 7, wherein the predefined rule comprises at least
one of:
a first empty region from the at least one empty region being the
preferred label location associated with the content, wherein the preferred
label location is part of metadata linked to the content;
selecting a second empty region closest to the preferred label
location associated with the content, when the preferred label location is
unavailable within the label; and
labeling guidelines from a regulatory authority for positioning the
content within a certain region of the label, based on the type of the content
and an end product for affixing the label.

9. The system of claim 7, wherein the at least one label attribute further
comprises pixel values associated with each pixel within the image of the
label, and
wherein to process the image of the label, the processor-executable
instructions further cause the processor (202) to extract the pixel values
using a pixel-by-pixel comparison-based algorithm, and
wherein to determine an empty region from the at least one empty
region within the label, the processor-executable instructions further cause
the processor (202) to determine a set of contiguous pixels, wherein each
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pixel in the set of contiguous pixels has a predefined pixel value, and
wherein the empty region comprises the set of contiguous pixels.
10. The system of claim 9, wherein to determine at least one empty region,
the processor-executable instructions further cause the processor (202) to:
identify a set of empty regions in the image of the label;
quantify dimensions of each of the set of empty regions;
compare dimensions of each of the set of empty regions with the
dimensions of the content;
identify the at least one empty region from the set of empty regions,
wherein dimensions of each of the at least one empty region is greater than
or equal to the dimensions of the content; and
modify the dimensions of the content to match the dimensions of a
largest empty region from the at least one empty region, when the
dimensions of the content does not match with the dimensions of each of
the at least one empty region.
11. The system of claim 7, wherein the at least one content attribute is
retrieved from the content using an image processing algorithm, and
wherein the at least one content attribute is retrieved from a library of
images, and wherein the library of images comprises mapping of a plurality
of contents with associated content attributes, and wherein the type of the
content comprises at least one of an icon, a text, an image, an emoji, a logo,
or a shape.
12. The system of claim 11, wherein the processor-executable instructions
further cause the processor (202) to:
generate the image of the label from the label; and convert the image to a size that is of the predefined ratio relative to
the label.