CLIAMS:We claim
1. A method for detecting one or more objects in a target area, comprising:
(a) capturing, by an object detection device, one or more video signals of the target area;
(b) converting, by the object detection device, the one or more video signals into a plurality of frames;
(c) computing, by the object detection device, first set of threshold values corresponding to the plurality of frames;
(d) generating, by the object detection device, a plurality of binary images from the first set of threshold values;
(e) computing, by the object detection device, second set of threshold values by analyzing the first set of threshold values;
(f) updating, by the object detection device, the first set of threshold values using the second set of threshold values and changing the first set threshold values as second set of threshold values; and
(g) analyzing, by the object detection device, the updated first set of threshold values for detecting the one or more objects and repeating steps (d), (e) and (f) until the one or more objects is detected.

2. The method as claimed in claim 1, wherein the detected one or more objects are displayed on a display unit by the object detection device.

3. The method as claimed in claim 1, wherein the plurality of binary images is converted into a predefined format for displaying on the display unit.

4. The method as claimed in claim 1, wherein the capturing of one or more video signals is performed on a real time.

5. The method as claimed in claim 1, wherein the first threshold values is computed from the plurality of frames using a selected window processing technique.

6. The method as claimed in claim 1, wherein generating the plurality of binary images further comprising:
assigning zero to binary value of the binary image when pixel value of each pixel in each plurality of frames is greater than the first threshold value of the corresponding frame; and
assigning one to the binary value of the binary image when pixel value of each pixel in each plurality of frames is one of lesser than and equal to the first threshold value of the corresponding frame.

7. An object detection device for detecting one or more objects in a target area, comprising:
a video capturing unit for capturing of one or more video signals of the target area;
a video decoder for converting the one or more video signals into a plurality of frames; and
a threshold calculating and updating unit, comprising:
a threshold calculation unit for computing first set of threshold values corresponding to the plurality of frames;
a binary image formation unit for generating a plurality of binary images from the first set threshold values;
an object detector for detecting the object in the target area; and
a threshold updating unit for computing second set of threshold values by analyzing the first set of threshold values and updating the first set of threshold values using the second set threshold values

8. The device as claimed in claim 7, further comprising a data storage unit for storing the plurality of frames.

9. The device as claimed in claim 7, further comprising a display unit to display the detected one or more objects.

10. The device as claimed in claim 7, further comprises a video decoder for converting the plurality of binary images into a predefined format for displaying on the display unit.
,TagSPECI:TECHNICAL FIELD
The present disclosure generally relates to detection of an object in a selected area, and more particularly the present disclosure relates to a real time detection of an object in a target area using an adaptive threshold technique.

BACKGROUND
Presently, there exists a method for extracting foreground objects from a currently observed image. The method comprises segmenting background objects of a previously observed image into regions of homogeneous brightness and setting initial threshold values for each segmented regions to initialize background image information. Also, the method comprises subtracting the currently observed image from the background image information. The method further comprises thresholding the image difference using the initial threshold values to extract foreground of the currently observed image and comparing the foreground of the currently observed image against foreground of the previously observed image to update the initial threshold values of the background image information. By this, the extraction of the foreground objects of the currently observed image is achieved.

In one conventional approach, a method for edge detection of an image with adaptive threshold which is also referred as canny edge detection filter is provided. The method comprises smoothing the image using a filter, determining a gradient magnitude and angle for each pixel of the image, performing non-maximum suppression and applying an upper threshold (T1) and a lower threshold (T2) for determining the edges in the image. The method approaches in obtaining the edges of the image as close as possible to the edge in the real image.

In another conventional approach, an apparatus to detect homogeneous region of image using adaptive threshold is disclosed. A homogeneous region detector detects an image using an adaptive threshold, comprises a global region standard deviation calculation part, a local region standard deviation calculation part and a homogeneous region determination part. The global region standard deviation calculation part calculates a global region standard deviation of a whole region of an input image. The local region standard deviation calculation part divides the input image into a predetermined number of local regions and to calculate a local region standard deviation of the each local region. The homogeneous region determination part separates the homogeneous region from a feature region in the input image using an adaptive threshold calculated based on entropy of the input image. Accordingly, the homogeneous region can be precisely detected by effectively separating the homogeneous region from the feature region of the input image by using the threshold adaptively calculated based on the entropy of the input image, so that the homogeneous region can be applied to various fields of image processing.

Though the above mentioned systems and methods provide detection of one of a region or an object by implementing different strategies, they do not disclose an aspect of detecting one or more objects in a target area in real time.

Accordingly, a need exists for a device and a method for detecting one or more objects in a target area in real time.

SUMMARY
One or more short comings of the prior art are overcome and additional advantages are provided through the present disclosure. Additional features and advantages are realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.

Embodiments of the present disclosure provide a method for detecting one or more objects in a target area in real time. The method includes capturing one or more video signals of the target area and converting into a plurality of frames. Also, the method includes computing first set of threshold values corresponding to the plurality of frames and generating plurality of binary images from the first set of threshold values. Further, the method includes computing second set of threshold values by analyzing the first set of threshold values and updating the first set of threshold values using the second set of threshold values and changing the first set threshold values as second set of threshold values, and analyzing the updated first set of threshold values for detecting the one or more objects. Furthermore, the method includes the generation of binary images, computing the second set of threshold values and updating the first set of threshold values repeats until one or more objects is detected.

Embodiments of the present disclosure provide an object detection device for detecting one or more objects in a target area comprising a video capturing unit, a video decoder and a threshold calculating and updating unit. The video capturing unit captures one or more video signals of the target area and the video decoder converts the one or more video signals into a plurality of frames. The threshold calculating and updating unit further comprises a threshold calculation unit, a binary image formation unit, an object detector and a threshold updating unit. The threshold calculation unit computes first set of threshold values corresponding to the plurality of frames. The binary image formation unit generates a plurality of binary images from the first set threshold values and the object detector for detecting the object in the target area. The threshold updating unit computes second set of threshold values by analyzing the first set of threshold values and updates the first set of threshold values using the second set threshold values

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects and features described above, further aspects, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
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. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:

Figure 1illustrates an exemplary block diagram of an object detection device, in accordance with an embodiment of the present disclosure;
Figure 2illustrates a block diagram of a threshold calculating and updating unit, in accordance with an embodiment of the present disclosure; and
Figure 3illustrates a flowchart illustrating a method of detecting one or more objects using an object detection device, in accordance with an embodiment of the present disclosure;

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION
The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. Additional features and advantages of the disclosure will be described hereinafter which form the subject of the claims of the disclosure. It should be appreciated by those skilled in the art that the conception and specific aspect disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure.

In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

Embodiments of the present disclosure provide an object detection device and a method for detecting one or more objects in a target area. The method includes capturing one or more video signals of the target area and converting into a plurality of frames. Also, the method includes computing first set of threshold values corresponding to the plurality of frames and generating plurality of binary images from the first set of threshold values. Further, the method includes computing second set of threshold values by analyzing the first set of threshold values and updating the first set of threshold values using the second set of threshold values and changing the first set threshold values as second set of threshold values and analyzing the updated first set of threshold values for detecting the one or more objects. Furthermore, the method includes the generation of binary images, computing the second set of threshold values and updating the first set of threshold values repeats until one or more objects is detected.

In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

Figure 1 illustrates an exemplary block diagram of an object detection device, in accordance with an embodiment of the present disclosure.

The object detection device (100), in accordance with the present disclosure relates to detecting or tracking of an object in real time. In one embodiment, the tracking may be aerial target tracking. The object detection device (100) comprises a video capturing unit (101), a video decoder (102), a data storage unit (103), a threshold calculation and updating unit (104), a video encoder (105) and an external device (107). The video capturing unit (101) captures video signals of the target area. The video signals are analog and may be in form of one of national television system committee (NTSC) and phase alternating line (PAL). The video signals are received by the video decoder (102) for digitization which is achieved by converting the video signals into plurality of frames where each frame may be a 16 bit digital data. In one embodiment, the digital data is in 4:2:2 YCbCr colour format. The plurality of frames is stored in the data storage unit (103) for further computation and analysis of the plurality of frames using a selected processing window. The data storage unit (103) stores any external data also. The threshold calculating and updating unit (104) is configured for computing first set of threshold values, generating binary images, computing second set of threshold values and updating the first set of threshold values for detecting an object.

In one embodiment, the data storage unit (103) and the threshold calculating and updating unit (104) are configured on aField-Programmable Gate Array (FPGA) which facilitates parallel processing in the device. When the object is detected, the binary image of detected object is converted in to a predefined format by the video encoder (105). In one embodiment, the conversion includes conversion of binary images to red, blue and green (RGB) format and further RGB format in to analog video graphics array (VGA) format used for displaying purpose. The external device (107) is configured to provide one or more commands and parameters required for the computation and updating of the first set of parameters. In one embodiment, the external device may be one of but not in a limiting of the scope, a mobile phone, a computer and a tablet. Further, the predefined format of signals of the tracked object from the video decoder (105) is displayed on the display unit (106).

Figure 2 illustrates a block diagram of a threshold calculating and updating unit, in accordance with an embodiment of the present disclosure;

The threshold calculating and updating unit (104) comprises of a threshold calculating unit (201), a binary image formation unit (202), an object detector (203) and a threshold updating unit (204). The threshold calculation unit (201) computes the first set of threshold values for the plurality of frames in the selected processing window. The computing of the first set of threshold values depends upon the video signals stored in the data storage unit 103 captured by video capturing unit (101). In one embodiment, the video capturing unit (101) may be one of thermal imaging (TI) camera and charge coupled device (CCD) camera. In one example embodiment, if the video capturing unit (101) is a TI camera, the first threshold value may be for one of black polarity target and white polarity target. For black polarity target, the binary image is generated by the binary image formation unit (202) by considering all input pixel values less than or equal to the first threshold value as binary value “1” and all input pixel values greater than the threshold value as binary value “0”. The binary image is formed in reverse manner for the white polarity target, that is all pixel values greater than or equal to the threshold value are given a binary value as “1” otherwise “0”. In another example embodiment, if the video capturing unit (101) is a CCD camera, two threshold limits are calculated, one for lower limit and the other for upper limit. The binary image is formed by considering all input pixel values as binary value “1” when the pixel value is outside the threshold limits and as binary value “0” for all the pixels within the threshold limits. The computation of the first set threshold values for the white target and the black target is done using equation 1 and 2.

TH_(1st_bl)=f1(I) ……….. (1)
TH_(1st_wt)=f2(I) .………. (2)
where,
f1(I),f2(I) are functions of image (I) characteristics.

Further, the plurality of binary images are generated and stored for analysis. The object detector (203) is configured to detect the object based on the plurality of binary images generated. The object detector (203) is also referred as a target detector. The computation of the second set of threshold values for updating the first set of threshold values is performed by the threshold updating unit (204).In one embodiment, the second set threshold values depend upon number of objects detected and their characteristics. The number of objects detected may be one of no objects and multiple objects. Also, the second set of threshold values depends upon the incremental and decremental components which may be varied in steps by one of manually and automatically. The variations of the thresholds are carried out iteratively until predefined values of the object to be detected are obtained by the object detector (203). The second set of threshold values for no objects detected is given by equations 3 and 4.The second set of threshold values for multiple objects detected is given by equations 5 and 6.

TH_(2nd_bl)=TH_(1st_bl)+ IC ……… (3)
TH_(2nd_wt)=TH_(2nd_wt)-DC …….… (4)
TH_(2nd_bl)=TH_(1st_bl)- IC ....…….. (5)
TH_(2nd_wt )=TH_(2nd_wt )+ DC ….……. (6)
where, IC is the incremental component and
DC is the decremental component.

In one embodiment, the incremental and decremental components are varied relatively in one of big steps and small steps based on strength in the plurality of binary images. When the strength is greater than a predefined value, then small steps is selected otherwise big steps is selected. In one embodiment, the incremental and decremental components are varied relatively in one of big steps and small steps based on number of objects detected. In an example embodiment, considering less number of objects detected, small steps are selected otherwise big steps are selected which leads in faster computation. The external device (107) in the object detection device is configured for initializing the incremental and decremental components. Also, the external device (107) is configured for selecting commands which include but not limited to adjustment of the selected processing window size, the video capturing unit selection and updating of the first set of threshold values. The iterative process of computation and updating the first set of threshold values will exist until the object is detected

Figure 3illustrates a flow diagram of methods involved in an object detection device, in accordance with an embodiment of the present disclosure.

Initially, for detection of the object by the object detection device (100), at step 301, the video capturing unit (101) captures the one or more video signals of the target area. At step 302, the one or more video signals are converted to the plurality of frames by the video decoder (102). At step 303, the first set of threshold values are computed by the threshold calculation unit (201) for the corresponding plurality of frames. At step 304, based on the first set of threshold values, the binary images are generated by the binary image formation unit (202). At step 305, the second set of threshold values are computed form the plurality of binary images and at step 306, the first set of threshold values are updated based on the second set of threshold value. At step 307, the object detector (203) detects for the object and if the object is tracked, at step 308, the object will be displayed on the display unit. Otherwise the process of generating the binary images from the updated first set of threshold values, computing the second set of threshold values and updating the first set of threshold values continues iteratively until the object is detected.

Embodiments of the present disclosure provide advantages of detecting of the objects by implementing an iterative process of adaptive threshold calculation based on the previous threshold values in real time.

The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.

The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise.

The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

The foregoing description of various embodiments of the invention has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. It is intended that the scope of the invention be limited not by this detailed description, but rather by the claims appended hereto. The above specification, examples and data provide a complete description of the manufacture and use of the composition of the invention. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention resides in the claims hereinafter appended.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral Numerals:
Reference Number Description
100 block diagram of an object detection device
101 video capturing unit
102 video decoder
103 data storage unit
104 threshold calculating and updating unit
105 video encoder
106 display
107 external device
200 block diagram of threshold calculating and updating unit
201 threshold calculating unit
202 binary image formation unit
203 object detector
204 threshold updating unit
301 capture video signals of target area
302 convert the video signals to plurality of frames
303 compute first set of threshold values for corresponding frames
304 generate binary images
305 compute second set of threshold values from the binary images
306 update first set of threshold values
307 check if object detected
308 display the detected object

We claim
A method for detecting one or more objects in a target area, comprising:
capturing, by an object detection device, one or more video signals of the target area;
converting, by the object detection device, the one or more video signals into a plurality of frames;
computing, by the object detection device, first set of threshold values corresponding to the plurality of frames;
generating, by the object detection device, a plurality of binary images from the first set of threshold values;
computing, by the object detection device, second set of threshold values by analyzing the first set of threshold values;
updating, by the object detection device, the first set of threshold values using the second set of threshold values and changing the first set threshold values as second set of threshold values; and
analyzing, by the object detection device, the updated first set of threshold values for detecting the one or more objects and repeating steps (d), (e) and (f) until the one or more objects is detected.

The method as claimed in claim 1, wherein the detected one or more objects are displayed on a display unit by the object detection device.

The method as claimed in claim 1, wherein the plurality of binary images is converted into a predefined format for displaying on the display unit.

The method as claimed in claim 1, wherein the capturing of one or more video signals is performed on a real time.

The method as claimed in claim 1, wherein the first threshold values is computed from the plurality of frames using a selected window processing technique.

The method as claimed in claim 1, wherein generating the plurality of binary images further comprising:
assigning zero to binary value of the binary image when pixel value of each pixel in each plurality of frames is greater than the first threshold value of the corresponding frame; and
assigning one to the binary value of the binary image when pixel value of each pixel in each plurality of frames is one of lesser than and equal to the first threshold value of the corresponding frame.

An object detection device for detecting one or more objects in a target area, comprising:
a video capturing unit for capturing of one or more video signals of the target area;
a video decoder for converting the one or more video signals into a plurality of frames; and
a threshold calculating and updating unit, comprising:
a threshold calculation unit for computing first set of threshold values corresponding to the plurality of frames;
a binary image formation unit for generating a plurality of binary images from the first set threshold values;
an object detector for detecting the object in the target area; and
a threshold updating unit for computing second set of threshold values by analyzing the first set of threshold values and updating the first set of threshold values using the second set threshold values

The device as claimed in claim 7, further comprising a data storage unit for storing the plurality of frames.

The device as claimed in claim 7, further comprising a display unit to display the detected one or more objects.

The device as claimed in claim 7, further comprises a video decoder for converting the plurality of binary images into a predefined format for displaying on the display unit.
Dated: this 31st day of March, 2015
SRAVAN KUMAR GAMPA
IN/PA – 1744
Of K&S PARTNERS
AGENT FOR THE APPLICANT

A METHOD FOR DETECTING AN OBJECT IN A TARGET AREA AND A DEVICE THEREOF
ABSTRACT

Embodiments of the present disclosure provide a device and a method for detecting one or more objects in a target area. The method includes capturing one or more video signals of the target area and converting into a plurality of frames. Further, the method includes computing first set of threshold values corresponding to the plurality of frames and generating corresponding plurality of binary images. Also, the method includes computing second set of threshold values by analyzing the first set of threshold values and updating the first set of threshold values using the second set of threshold values and analyzing the updated first set of threshold values for detecting the one or more objects. The method involving the generation of binary images, computing the second set of threshold values and updating the first set of threshold values repeats until one or more objects is detected.

Figures 2