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"A Camera And Method Of Selecting/Detecting Image"

Abstract: There is disclosed a camera, comprising an image input in the camera to obtain image information from an image; a storage medium in the camera to store at least one user-input image metric threshold associated with the image; and a processing unit in the camera to generate at least one image metric from the obtained image information, to compare the at least one image metric to the at least one user-input image metric threshold, and to initiate a capture sequence for the image input to capture the image if the at least one image metric exceeds the at least one user-input image metric threshold, wherein the processing unit is coupled to the image input and the storage medium.

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Notices, Deadlines & Correspondence

Patent Information

Application #
Filing Date
23 November 1998
Publication Number
48/05
Publication Type
INA
Invention Field
GENERAL ENGINEERING
Status
Email
Parent Application
Patent Number
Legal Status
Grant Date
2007-02-09
Renewal Date

Applicants

INTEL CORPORATION
2200 MISSION COLLEGE BOULEVARD, SANTA CLARA, CALIFORNIA 95052

Inventors

1. RANDY L DUNTON
16026 S 14TH DRIVE, PHOENIX ARIZONA 85045
2. LOWRENCE L BOOTH
15230 S 17TH AVENUE ,PHOENIX ,ARIZONA 85045

Specification

I. Field of the Invention
The described invention relates to a camera and method of selecting/detecting
image. In particular, the invention relates to an image capture system facilitating
selection of an image based on the content of the image.
2. Description of Related Art
Image capture devices, such as still and video cameras, typically have stored
images based upon the input of a.trigger from the user. Sometimes the trigger is
manually input, for example, by pushing a button. The trigger may alternatively be
triggered remotely via a coupling to. a flash strobe, or through a timer.
Some events, however, are very difficult to trigger upon. As an example,
capturing an image of lightning during a lightning storm is very difficult to capture
because of the unpredictability of the event, as well as the quick timing that is needed to
capture the event.
One way in which lightning could be captured is by taking a video picture of the
sky, and hoping that lightning strikes during the time the video is capturing images (the
capture period). However, this method fails in several respects.
First, the quality of video is typically not as good as that of a still picture.
Second, because the video image must be stored, the capture period is limited to the
amount of storage space in the camera. This is restrictive when the target image may take
a very iong time to happen. Finally, a person has to either be present during the capture
period to observe whether lightning had struck to know whether the target image was
captured, or the user potentially has to review the entire video to see whether the desired
event occurred. A more automated method of detecting a target image is desirable.
SUMMARY OF THE INVENTION
An image capture system comprises an image input and processing unit. The
image input obtains image information which is then passed to the processing unit. The
processing unit determines an image metric from the image information. The processing
unit initiates a capture sequence when the image metric meets a predetermined condition.
The capture sequence may store one or more images, or it may indicate that one or more
images have been detected. In one embodiment, the image input comes from an image
sensor, such as a CMOS or CCD sensor. In another embodiment, the image input comes
from a video stream.

Accordingly, the present invention provides a camera, comprising :
an image input in the camera to obtain image information from an image;
a storage medium in the camera to store at least one user-input image metric
threshold associated with the image; and
a processing unit in the camera to generate at least one image metric from the
obtained image information, to compare the at least one image metric to the at least
one user-input image metric threshold, and to initiate a capture sequence for the image
input to capture the image if the at least one image metric exceeds the at least one
user-input image metric threshold, wherein the processing unit is coupled to the image
input and the storage medium.

ACCOMPANYING
BRIEF DESCRIPTION OF THE/DRAWINGS
Figure 1 shows an image capture system in accordance with one embodiment of
the invention.
Figure 2 shows another embodiment of an image capture system.
Figure 3 shows a representation of an image sampled by the image capture device
201.
Figure 4 shows a representative histogram of the luminosity corresponding to the
image of Figure 3.
Figure 5 shows a representation of an image that was created via a computer
program.
Figure 6 shows a representative histogram of the luminosity corresponding to the
image of Figure 5.
Figure 7 shows an embodiment of a triggering mechanism.
Figure 8 shows an example of an interface that may be used on the image capture
device.
Figure 9 shows a graphical interface in which various thresholds are identified at
several levels of an image metric.
Figure 10 shows an example of a trigger system set up to measure the blue
component of an image.
DETAILED DESCRIPTION
An apparatus and method for determining when one or more images match an
image profile are described. In a first embodiment, the images are sampled by an image
sensor in a camera. The image profile comprises one or more thresholds of image
metrics such as color content and light intensity information. The images from the image
sensor are processed and compared against the image metrics of the image profile. If a
match is found, as will be described later, then the camera triggers a capture sequence in
which one or more images are saved to a storage medium. The capture sequence may
save a single image, or if desired, the capture sequence may save multiple images. If
images are buffered, images sampled prior to the trigger of the capture sequence can also
be saved to the storage medium, as will be described in more detail later.
In a second embodiment, the images are provided from a collection of images or a
video stream, for example, a television signal, VCR output, or digital video diskette
(DVD) output. The images from the video stream are processed and compared against
the image metric thresholds set up in the image profile to find a match. This is useful for
searching a video stream for a particular image. For example, after a video camera is
used to capture images, this second embodiment can be used to automatically determine

whether a desired image is within the capture period. This frees the user from having to
be present during the capture period.
When an image matches the image profile, i.e., all thresholds are reached, a
capture sequence is initiated. This may result in one or more images being stored to a
storage medium, or it may result in an indication that the image was found in the video
stream. Information about the location or a time index of the identified image may also
be saved.
Image metrics are derived from various components of an image. In one
embodiment image metrics include, but are not limited to, color content and light intensity
information. Examples of triggering a capture sequence based upon color content
follow. A camera focused on a tree can detect when a bluebird enters the image by
triggering on the blue content in the image. When the blue content exceeds a specified
threshold set up in the image profile, an image capture is triggered. Similarly, the camera
can be set up to trigger on the bluebird leaving the image by monitoring the blue content
in the image and triggering a capture sequence when the blue content falls below a
specified threshold. The blue content can be further specified to trigger only upon a
particular shade of blue in order to capture images of only a particular bluebird, or a
particular species of bluebird.
In a preferred embodiment, the thresholds of the image metric(s) that comprise
the image profile can be programmed via an interface. The image profile can be set to
readily match one or more color metrics of an image, or the image profile may be set so
that there is rarely a match with the one or more color metrics of an image. For example,
the trigger may be set up so that minor variations in image content will not trigger a
capture sequence.
The image profile can also be set up based upon a rate of change of an image
metric. For example, lightning is characterized by a rapid change in light intensity, or
luminosity. An image of lightning may be captured by specifying a rate of change of
luminosity in the image profile. When the detected rate of change of luminosity exceeds
the specified rate of change of the image profile, a capture sequence is initiated.
However, a slow rate of change of luminosity corresponding, for example, to a sunrise
or a sunset can be set up to not trigger a capture sequence.
Figure 1 shows an image capture system 100 in accordance with one embodiment
of the invention. The image capture system includes an image input 102, an image
processing unit 104, a processor 120, and a storage medium 140.
The image input 102 captures image information using technology that is well
known in the art. In one embodiment, the image input 102 is a complementary metal
oxide semiconductor (CMOS) sensor. However, the image input 102 could alternatively

be a charge couple device (CCD) sensor or other type of image sensor. The image input
may also be an interface which receives a video stream from a television, satellite
broadcast, VCR, or other digital video recording. The image input 102 is coupled to
provide image information to the image processing unit 104. Image processing unit 104
may include color look up tables for adjusting color values to pixel data. The image
processing unit 104 may also include a compression unit for compressing the image
information. In one embodiment, a data flow manager 108 couples the image processing
unit 104 to a bus 110.
In one embodiment, processor 120, histogram unit 130, and storage medium 140
are coupled to bus 110. The processor 120 is coupled to receive instructions from
firmware (or alternatively memory) 122 for instructing the processor what operations to
perform. The processor optionally is also coupled to timer 124 which provides a timing
input so that processor 120 can determine a rate of change of the image metric(s)
generated by the histogram unit 130, as will be explained next. In one embodiment,
memory unit 126 is coupled to processor 120 for storing the image profile which
includes one or more threshold values of image metric(s). The threshold values are
compared against the image metric(s) generated by the histogram unit 130. *
Histogram unit 130 is coupled to receive image information from the image
processing unit 104. In one embodiment, the data flow manager 108 transfers the image
information to the histogram unit 130, and the histogram unit 130 determines one or
more image metrics from the image information. The data flow manager may be a DMA,
as one example. In one embodiment, the histogram unit generates colorimetric data such
as the amount of red, green, and blue (RGB) components. Alternatively, the histogram
unit 130 can determine other colorimetric data. For example, it can determine cyan,
magenta, yellow, and light intensity (CMYK) data. The histogram unit 130 may also
determine photometric data. Photometric data includes light intensity, or luminosity,
measured in either absolute or relative scales. However, the image metrics are not limited
to color and light intensity; other image metrics can be determined from the image
information. In one embodiment, the image information is temporarily stored in memory
132 while the histogram unit 130 determines image metrics.
The processor 120 compares the image metrics generated by the histogram unit
130 with its image profile. In one embodiment, for each image metric, the image profile
indicates a threshold value and whether a match for that image metric is met according to
whether the measured image metric is below or above the threshold. Alternatively, for
each image metric, two thresholds may be specified, with a match occurring only if the
measured image metric is above a first threshold and below a second threshold.
Threshold levels will be,discussed in more detail later.

Storage medium 140 is used to store the image information when the image
metrics determined from the image information matches the image profile, i.e., all
thresholds are met. In one embodiment, one or more images are temporarily stored in
memory area 132 prior to being stored to storage medium 140. By buffering the images
into memory area 132, the images prior to finding a capture sequence can be saved. In
one embodiment, various combinations of the firmware 122 and memories 122, 126,
132, and 140 may be combined together within a single unit.
External interface 160 is can be used for downloading the saved images from
storage medium 140. External interface 160 can also be used to input the image profile.
Figure 2 shows an alternate embodiment of an image capture system 200. Image
capture portion 201 includes an image input 202, processor 220, firmware 222, and
timer 224 that are similar to their counterparts of the same name in Figure 1. Image
metering unit 204 incorporates image processing unit 104, data flow manager 108, and
histogram unit 130. A host personal computer is coupled to the image metering unit 204
via a communication link 265.
The host personal computer may provide the input of the image profile to the
image capture portion 201 via the communication link 265. In one embodiment, a
storage medium can be included in host personal computer 270 so that it need not reside
in the image capture portion 201. The host personal computer 270 may also implement
the histogram unit 130 function in software or hardware.
Triggering a capture sequence
Figure 3 shows a representation of an image of a night-time scene sampled by the
image capture device 201. Figure 4 shows a representative histogram of the luminosity
corresponding to the image of Figure 3. On the horizontal axis is the level of the
luminosity. On the vertical axis is the count of the luminosity per each level.
In one embodiment, a background image such as Figure 3 is captured by the
image capture device 201. A histogram of the image determines image metric(s) which
are then compared to subsequent sampled images. An image profile is generated having
one or more thresholds associated with the image metric(s) of the background image.
Figure 7 shows an embodiment of a triggering mechanism. At block 700, a
histogram of image data is determined. At block 705, the count of one or more levels of
the luminosity is compared against an image profile derived from the histogram of the
background image. At decision block 710, if the counts of the one or more levels of the
luminosity are greater than the image profile thresholds, then a capture sequence is
initiated (block 715). However, if the comparisons are not all greater than the typical
background image, then another image is sampled (block 720).

The image profile thresholds can be preset to any amount or percentage above the
typical background image. For example, it can be set to 5%, or 10% above the typical
background image. Alternatively, it could be set at a preset amount or percentage less
than typical background image.
Figure 8 shows an example of an interface that may be used with the image
capture device. A "SBI" button 802 for sampling the background image generates a
histogram and image metrics for a background image. Preset variations based on the
background image can be easily chosen by selecting a few buttons: one set of buttons
804 indicating a threshold "greater than" or "less than" the histogram of the background
image, one set of buttons 806 indicating by how much (5%, 10%, or 20%), and one set
of buttons 808 indicating which image metric(s) to compare. The image metrics, for
example, may include red, green, blue, and luminosity.
The interface for inputting complex threshold data via buttons, however, may be
restrictive. Thus, using a graphical interface may be more suited to the task.
Figure 9 shows a graphical interface in which various thresholds are identified for
several levels of an image metric. For the thresholds labeled as '>', a capture sequence is
triggered when an image metric at that level has a measured count above the" threshold.
For the thresholds labeled as '<', a capture sequence is triggered when an image metric at
that level has a measured count below the threshold.
As an example, Figure 9 shows a first image metric 900 that is set up to trigger a
capture sequence when the measured count for that image metric is above the threshold
902. A second image metric 910 is set up to trigger a capture sequence when the
measured count for that image metric is below the threshold 912. A uiird image metric
920 is set up to trigger a capture sequence when the measured count for that image metric
is below the threshold 924 but above the threshold 922, and a fourth image metric 930 is
set up to trigger a capture sequence when the measured count for that image metric is
above the threshold 934 or below the threshold 932. In one embodiment, all of the
image metric (e.g., 900, 910, 920 and 930) threshold requirements must be met to
trigger the capture sequence. In another embodiment, only one or any combination of
image metric (e.g., 900, 910, 920, or 930) threshold requirements needs to be met to
trigger the capture sequence.
In one embodiment, the camera includes an interface such as an LCD screen and
either buttons or a graphical interface so that the image profile thresholds can be entered
into the camera.
One method of generating an image profile suitable for initiating a capture
sequence creates a mock up image that looks similar to the desired image. The mock up
image can be created, for example, by using software to modify a background image.

Alternatively, an image similar to that desired can be scanned into a computer, using
well-known techniques. A histogram can then be generated from the mock up image
using either software or hardware to model the histogram. The histogram of the mock up
image can then be compared against the histogram of a background image captured by the
image capture device. One or more thresholds based on the image metric(s) of the
histograms can be set up so that a desired image will initiate a capture sequence.
For example, Figure 5 shows a representation of an example of an image that was
created via a computer program. Figure 6 is a representative histogram of the luminosity
corresponding to the image of Figure 5. In one embodiment, a background image is
taken with the image capture device 201. The image is modified on host computer 270.
A histogram of both the background image and the modified image are created using
software residing on the host computer 270. The two histograms are compared against
each other to determine which image metric(s) are best suited for use as a threshold to
initiate a capture sequence.
In the case of Figures 5 and 6, which correspond to lightning striking during the
night, the count of the luminosity is clearly much higher at several levels than that of
Figures 3 and 4.
In one embodiment, a user manually determines one or more the image metric
thresholds. In another embodiment, software determines the image metric threshold(s)
by comparing the two or more histograms. The software determines one or more levels
in the histograms in which the two image metrics differ the greatest. The software then
creates one or more thresholds from the background image, making sure that the
threshold is above the background image and allowing a margin to account for noise.
The host computer 270 then communicates the threshold information to the image capture
device 201. The host computer can then be disconnected from the image capture device
201, if desired.
Figure 10 shows an example of an image capture system set up to initiate a
capture sequence based on the image metric of color content. This example initiates the
capture sequence based on blue content. However, the image profile can be set up based
on other colorimetric or photometric data.
The image information is obtained at block 1000. At block 1002 the image
information is broken down into red, green and blue components. At block 1004, the
blue component of the image data is processed to provide image metrics for the blue
component. At block 1006, the blue component metrics are compared against the image
profile. If the blue image Tnetric(s) meet each of the one or more image profile thresholds
(i.e., match the image profile) then the image is captured at block 1010. If at block 1008,
the blue image metric(s) do not meet all of the one or more thresholds, then the image is

not captured. Instead, the flow sequence restarts at block 1000, and image information
from another image is obtained.
Thus, an apparatus and method determining when one or more images meet an
image profile is disclosed. The specific arrangements and methods described herein are
merely illustrative of the principles of this invention. Numerous modifications in form
and detail may be made without departing from the scope of the described invention.
Although this invention has been shown in relation to a particular embodiment, it should
not be considered so limited. Rather, the described invention is limited only by the scope
of the appended claims.

WE CLAIM:
1. A camera, comprising :
an image input in the camera to obtain image information from an image;
a storage medium in the camera to store at least one user-input image metric
threshold associated with the image; and
a processing unit in the camera to generate at least one image metric from the
obtained image information, to compare the at least one image metric to the at least
one user-input image metric threshold, and to initiate a capture sequence for the image
input to capture the image if the at least one image metric exceeds the at least one
user-input image metric threshold, wherein the processing unit is coupled to the image
input and the storage medium.
2. The camera as claimed in claim 1, wherein the at least one-user-input image
metric threshold is related to photometric data.
3. The camera as claimed in claim 1, wherein the at least one user-input image
metric threshold is related to light intensity information.
4. The camera as claimed in claim 1, wherein the at least one user-input image
metric threshold comprises a rate of change of the intensity information.
5. The camera as claimed in claim 1, wherein the at least one user-input image
metric threshold is related to colorimetric data.
6. The camera as claimed in claim 1, wherein the at least one user-input image
metric threshold comprises a rate of change of the colorimetric data.
7. The camera as claimed in claim 1, wherein there is provided a port to receive
parameters specifying the user-input image metric threshold.
8. The camera as claimed in claim 1, wherein there is provided an interface to
receive input of the user-input image metric threshold.
9. The camera as claimed in claim 1, wherein the image input has an image
sensor
10 A method of selecting an image, the method comprising the steps of:
(a) specifying an image profile;
(b) generating a histogram from an input image;
(c) determining whether the histogram of the input image matches the image
profile;
(d) if the histogram of the step

Documents

Application Documents

# Name Date
1 2058-CAL-1998-11-01-2023-RENEWAL AND CLAIMS.pdf 2023-01-11
1 2058-CAL-1998-LETTER OF PATENT CERTIFICATE-[09-02-2007].pdf 2007-02-09
2 2058-cal-1998-priority document.pdf 2011-10-07
2 2058-CAL-1998-RELEVANT DOCUMENTS [28-03-2019(online)].pdf 2019-03-28
3 2058-CAL-1998-RELEVANT DOCUMENTS [30-03-2018(online)].pdf 2018-03-30
3 2058-cal-1998-granted-specification.pdf 2011-10-07
4 Form 27 [31-03-2017(online)].pdf 2017-03-31
4 2058-cal-1998-granted-form 2.pdf 2011-10-07
5 Form 27 [15-03-2017(online)].pdf 2017-03-15
5 2058-cal-1998-granted-drawings.pdf 2011-10-07
6 2058-cal-1998-granted-description (complete).pdf 2011-10-07
6 201700-FORM 27-210316.pdf 2016-06-22
7 2058-cal-1998-granted-claims.pdf 2011-10-07
7 2058-CAL-1998-(27-03-2015)-FORM-27.pdf 2015-03-27
8 2058-cal-1998-granted-abstract.pdf 2011-10-07
8 2058-CAL-1998-(25-03-2013)-FORM-27.pdf 2013-03-25
9 02058-cal-1998-priority document.pdf 2011-10-07
9 2058-CAL-1998-FORM-27-1.pdf 2012-08-01
10 02058-cal-1998-letters patent.pdf 2011-10-07
10 2058-CAL-1998-FORM-27.pdf 2012-07-11
11 02058-cal-1998-abstract.pdf 2011-10-07
11 02058-cal-1998-g.p.a.pdf 2011-10-07
12 02058-cal-1998-assignment.pdf 2011-10-07
12 02058-cal-1998-form-5.pdf 2011-10-07
13 02058-cal-1998-claims.pdf 2011-10-07
13 02058-cal-1998-form-3.pdf 2011-10-07
14 02058-cal-1998-correspondence.pdf 2011-10-07
14 02058-cal-1998-form-2.pdf 2011-10-07
15 02058-cal-1998-description(complete).pdf 2011-10-07
15 02058-cal-1998-form-1.pdf 2011-10-07
16 02058-cal-1998-drawings.pdf 2011-10-07
17 02058-cal-1998-form-1.pdf 2011-10-07
17 02058-cal-1998-description(complete).pdf 2011-10-07
18 02058-cal-1998-form-2.pdf 2011-10-07
18 02058-cal-1998-correspondence.pdf 2011-10-07
19 02058-cal-1998-claims.pdf 2011-10-07
19 02058-cal-1998-form-3.pdf 2011-10-07
20 02058-cal-1998-assignment.pdf 2011-10-07
20 02058-cal-1998-form-5.pdf 2011-10-07
21 02058-cal-1998-abstract.pdf 2011-10-07
21 02058-cal-1998-g.p.a.pdf 2011-10-07
22 02058-cal-1998-letters patent.pdf 2011-10-07
22 2058-CAL-1998-FORM-27.pdf 2012-07-11
23 02058-cal-1998-priority document.pdf 2011-10-07
23 2058-CAL-1998-FORM-27-1.pdf 2012-08-01
24 2058-cal-1998-granted-abstract.pdf 2011-10-07
24 2058-CAL-1998-(25-03-2013)-FORM-27.pdf 2013-03-25
25 2058-cal-1998-granted-claims.pdf 2011-10-07
25 2058-CAL-1998-(27-03-2015)-FORM-27.pdf 2015-03-27
26 2058-cal-1998-granted-description (complete).pdf 2011-10-07
26 201700-FORM 27-210316.pdf 2016-06-22
27 Form 27 [15-03-2017(online)].pdf 2017-03-15
27 2058-cal-1998-granted-drawings.pdf 2011-10-07
28 Form 27 [31-03-2017(online)].pdf 2017-03-31
28 2058-cal-1998-granted-form 2.pdf 2011-10-07
29 2058-CAL-1998-RELEVANT DOCUMENTS [30-03-2018(online)].pdf 2018-03-30
29 2058-cal-1998-granted-specification.pdf 2011-10-07
30 2058-CAL-1998-RELEVANT DOCUMENTS [28-03-2019(online)].pdf 2019-03-28
30 2058-cal-1998-priority document.pdf 2011-10-07
31 2058-CAL-1998-11-01-2023-RENEWAL AND CLAIMS.pdf 2023-01-11
31 2058-CAL-1998-LETTER OF PATENT CERTIFICATE-[09-02-2007].pdf 2007-02-09

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