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Digital Camera Patent Abstract
A method and apparatus for automatically categorizing images in
a digital camera is provided. In one aspect, a digital camera includes
a processor that converts raw image data into processed image data
at the time of image capture, an analysis module coupled to the
processor that analyzes the raw image data at the time of image
capture and identifies one or more categories to which each of the
images may relate, and category tags that are attached to and stored
in each of the images corresponding to the categories. By attaching
and storing the category tags with each of the images, the processor
can automatically sort the images by their respective categories.
Digital Camera Patent Claims
What is claimed is:
1. A digital camera that captures raw image data of a live view
subject, the digital camera comprising: a processor within the digital
camera for converting the raw image data into processed image data
at the time of image capture; an analysis module coupled to the
processor and configured to analyze the raw image data at the time
of image capture in order to identify one or more categories to
which each of the images may relate; and category tags attached
by the analysis module to each of the images corresponding to the
categories, the category tags stored with each of the images, thereby
enabling the processor to automatically sort the images into different
categories.
2. The digital camera of claim 1 wherein the analysis module includes
one or more analysis algorithms for identifying the different categories.
3. The digital camera of claim 2 wherein the analysis module includes
combination logic for combining analysis results from the analysis
algorithms.
4. The digital camera of claim 1 wherein the analysis module includes
parametric controls for controlling the analysis module.
5. The digital camera of claim 1 wherein the analysis module is
selectively loaded into a volatile memory from a removable memory.
6. The digital camera of claim 1 further comprising a plurality
of analysis modules.
7. The digital camera of claim 1 wherein each of the images are
stored as image data contained in individual image files.
8. The digital camera of claim 7 wherein the category tags are
stored with the image data in the individual image files.
9. The digital camera of claim 1 further comprising an image processing
backplane communicating with image processing modules.
10. The digital camera of claim 9 further comprising one or more
insertion points between the image processing modules for inserting
the analysis module to analyze the images.
11. The digital camera of claim 10 wherein a selectable plurality
of analysis modules are inserted into the one or more insertion
points.
12. The digital camera of claim 10 further comprising an RGB insertion
point and a YCC insertion point.
13. The digital camera of claim 1 wherein the analysis module is
configured to recognize and label the images that match predetermined
criteria.
14. The digital camera of claim 1 wherein the analysis module is
configured to access and categorize the images after the images
have been processed and stored into a storage device.
15. The digital camera of claim 1 wherein the processor sorts the
images by accessing and analyzing the category tags attached to
each of the images.
16. The digital camera of claim 1 wherein the different categories
include human images and nature images.
17. The digital camera of claim 1 wherein the different categories
include city images and water images.
18. The digital camera of claim 1 further including image files
for storing the processed image data, the image files having locations
for image tags, wherein the image tags include the capture tags.
19. The digital camera of claim 1 wherein the category tags are
generated by the analysis module after the analysis module examines
the image data.
20. A method for automatically categorizing images in a digital
camera that captures raw image data from a live view subject, the
method comprising: converting the raw image data into processed
image data with a processor within the digital camera at the time
of image capture; analyzing the raw image data with an analysis
module at the time of image capture in order to identify one or
more categories to which each of the images may relate; running
the analysis module with the processor; attaching category tags
corresponding to the categories to each of the images with the analysis
module, thereby enabling the processor to automatically sort the
images into different categories; and storing the category tags
with the images.
21. The method of claim 20 wherein the analysis module includes
one or more analysis algorithms for identifying the different categories.
22. The method of claim 21 wherein the analysis module includes
combination logic for combining analysis results from the analysis
algorithms.
23. The method of claim 20 wherein the analysis module includes
parametric controls for controlling the analysis module.
24. The method of claim 20 wherein the analysis module is selectively
loaded into a volatile memory from a flash disk.
25. The method of claim 20 further comprising a plurality of analysis
modules.
26. The method of claim 20 wherein the images each are stored as
image data contained in individual image files.
27. The method of claim 26 wherein the category tags are stored
with the image data in the individual image files.
28. The method of claim 20 further comprising an image processing
backplane communicating with image processing modules.
29. The method of claim 28 further comprising one or more insertion
points between the image processing modules for inserting the analysis
module to analyze the images.
30. The method of claim 29 wherein a selectable plurality of analysis
modules are inserted into the one or more insertion points.
31. The method of claim 29 further comprising an RGB insertion
point and a YCC insertion point.
32. The method of claim 20 wherein the analysis module is configured
to initially recognize and label the images that match predetermined
criteria immediately upon capture of the images.
33. The method of claim 20 wherein the analysis module is configured
to access and categorize the images after the images have been processed
and stored into a storage device.
34. The method of claim 20 wherein the processor sorts the images
by accessing and analyzing the category tags attached to each of
the images.
35. The method of claim 20 wherein the different categories include
human images and nature images.
36. The method of claim 20 wherein the different categories include
city images and water images.
37. A digital camera that captures raw image data from a live view
subject, the digital camera comprising: means for converting the
raw image data into processed image data at the time of image capture,
whereby the means for converting is within the digital camera; means
for analyzing the raw image data at the time of image capture in
order to identify one or more categories to which each of the images
may relate; means for running the means for analyzing; means for
attaching category tags corresponding to the categories to each
of the images, thereby enabling the means for running to automatically
sort the images into different categories; and means for storing
the category tags with each of the images.
38. A computer-readable medium comprising program instructions
for automatically categorizing images with a digital camera that
captures raw image data from a live view subject, the program instructions
for: converting the raw image data into processed image data at
the time of image capture with a processor within the digital camera;
analyzing the raw image data at the time of image capture with an
analysis module in order to identify one or more categories to which
each of the images may relate; running the analysis module with
the processor; attaching category tags corresponding to the categories
to each of the images with the analysis module, thereby enabling
the processor to automatically sort the images into different categories;
and storing the category tags with each of the images.
Digital Camera Patent Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation-in-part of U.S. patent
application Ser. No. 09/430,235, entitled "Method and Apparatus
for Managing Image Categories in a Digital Camera to Enhance Performance
of a High-Capacity Image Storage Media," (P153CIP) filed on
Oct. 29, 1999, now issued as U.S. Pat. No. ______, which is a continuation-in-part
of U.S. patent application Ser. No. 09/121,760 filed on Jul. 23,
1998, entitled "System and Method for Automatic Analysis and
Categorization of Images in an Electronic Imaging Device,"
(P153CPA) now abandoned, each assigned to the assignee of the present
application.
FIELD OF THE INVENTION
[0002] This invention relates generally to electronic data processing,
and relates more particularly to a system and method for the automatic
analysis and categorization of images in an electronic imaging device.
BACKGROUND OF THE INVENTION
[0003] The efficient manipulation of captured image data is a significant
consideration for designers, manufacturers, and users of electronic
imaging devices. Contemporary imaging devices such as digital cameras
effectively enable users to capture images, assemble or edit the
captured images, exchange the captured images electronically, or
print a hard copy of the captured images. users to capture images,
assemble or edit the captured images, exchange the captured images
electronically, or print a hard copy of the captured images.
[0004] As a camera user captures a number of digital images, it
typically becomes necessary to sort and categorize the digital images.
In some systems, a camera user must resort to the cumbersome and
time-consuming task of individually viewing each captured image,
identifying various groupings of image categories, and somehow manually
tagging each image to specify the particular image category. For
example, in Parulski, U.S. Pat. No. 5,633,678, a camera user manually
selects a category for a group of images prior to the capture of
the images. The camera user must select a new category for each
new group of images. Such a manual categorization system is awkward
to use and, therefore, does not provide as efficient an imaging
device as a camera that features an automatic categorization system.
[0005] In other systems, software programs are available to permit
the user to create thumbnails (smaller renditions of the captured
image) and to place the thumbnails, with references to the original
images, into various libraries or category systems. This process
may also become very time consuming, especially as the number of
captured images or the variety of category types increases.
[0006] From the preceding discussion, it becomes apparent that
an electronic imaging system that manually analyzes and categorizes
any significant number of captured images does not achieve an acceptable
degree of efficiency. Therefore, an electronic imaging device that
automatically analyzes captured images, and then responsively categorizes
the analyzed images into one or more selected image groupings, would
clearly provide a significant improvement in efficient functionality
for various contemporary electronic imaging technologies.
[0007] For all the foregoing reasons, an improved system and method
are needed for the automatic analysis and categorization of images
in an electronic imaging device.
SUMMARY OF THE INVENTION
[0008] A method and apparatus for automatically categorizing images
in a digital camera is provided. In one aspect, a digital camera
includes a processor that converts raw image data into processed
image data at the time of image capture, an analysis module coupled
to the processor that analyzes the raw image data at the time of
image capture and identifies one or more categories to which each
of the images may relate, and category tags that are attached to
and stored in each of the images corresponding to the categories.
By attaching and storing the category tags with each of the images,
the processor can automatically sort the images by their respective
categories.
[0009] In the preferred embodiment, after the image data is converted
into RGB format, selected analysis modules may connect through an
RGB insertion point to advantageously analyze the image data at
an RGB transition point, in accordance with the present invention.
Once a particular analysis module analyzes the final line of the
image data, then that analysis module preferably generates any appropriate
category tags and stores the generated category tags into a blank
category tag location in the image file. The digital camera may
then subsequently access the stored category tags to automatically
categorize and utilize the individual stored images (which each
correspond to a separate image file).
[0010] Next, another image processing module preferably performs
gamma correction and color space conversion on the image data. The
image processing module also preferably converts the color space
format of the image data. In the preferred embodiment, the image
data is converted into YCC 444 format.
[0011] After the image data is converted into YCC 444 format, selected
analysis modules may be plugged into a YCC insertion point to analyze
the image data at a YCC transition point, in accordance with the
present invention. As discussed above, once a particular analysis
module analyzes the final line of the image data, then that analysis
module preferably generates any appropriate category tags and stores
the generated category tags into a blank category tag location in
the image file for subsequent use by the camera to automatically
categorize captured images. In other embodiments of the present
invention, analysis modules may readily analyze image data at any
other time or insertion point within the camera.
[0012] Next, an image processing module preferably performs a sharpening
procedure on the image data, and also may perform a variety of other
processing options. Then, an image processing module preferably
decimates the image data, and the image data is compressed into
a final image format (preferably JPEG.) Next, a file formatter preferably
formats the compressed image file, and the resulting image file
is finally saved into a removable memory device.
[0013] The image file thus includes any appropriate category tags,
and the camera may then subsequently utilize the category tags to
automatically access selected images, in accordance with the present
invention. The present invention therefore provides an efficient
system and method for automatically analysis and categorization
of captured images in an electronic imaging device.
DESCRIPTION OF THE DRAWINGS
[0014] FIG. 1 is a block diagram of one embodiment for a digital
camera, according to the present invention;
[0015] FIG. 2 is a block diagram of one embodiment for the imaging
device of FIG. 1, according to the present invention;
[0016] FIG. 4 is a rear elevation view of one embodiment for the
FIG. 1 digital camera;
[0017] FIG. 5 is a diagram one embodiment for the non-volatile
memory of FIG. 3, according to the present invention;
[0018] FIG. 6 is a diagram of one embodiment for the dynamic random-access
memory of FIG. 3, according to the present invention;
[0019] FIG. 7 is a diagram of one embodiment for a single analysis
module of FIG. 6, according to the present invention;
[0020] FIG. 8 is a diagram of one embodiment for an image file,
in accordance with the present invention;
[0021] FIG. 9 is a diagram of one embodiment for the image tags
of FIG. 8; and
[0022] FIG. 10 is a flowchart for one embodiment of method steps
to automatically analyze and categorize images, according to the
present invention.
DESCRIPTION OF THE INVENTION
[0023] The present invention relates to an improvement in digital
imaging devices, including digital cameras. The following description
is presented to enable one of ordinary skill in the art to make
and use the invention and is provided in the context of a patent
application and its requirements. Although the present invention
will be described in the context of a digital camera, various modifications
to the preferred embodiment will be readily apparent to those skilled
in the art and the generic principles herein may be applied to various
other embodiments. That is, any imaging device, which captures image
data, could incorporate the features described hereinbelow and that
device would be within the spirit and scope of the present invention.
Thus, the present invention is not intended to be limited to the
embodiment shown, but is to be accorded the widest scope consistent
with the principles and features described herein.
[0024] The present invention comprises one or more analysis modules
that examine captured image files for selected criteria. The analysis
modules then responsively generate and store appropriate category
tags along with the image file to advantageously enable the imaging
device to subsequently access the stored category tags and thereby
automatically access desired categories of captured images.
[0025] Referring now to FIG. 1, a block diagram of one embodiment
for a digital camera 110 is shown. Camera 110 preferably comprises
an imaging device 114, a system bus 116, and a camera computer 118.
Imaging capture device 114 may be optically coupled to an object
112 and electrically coupled via system bus 116 to camera computer
118. Once a user has focused imaging capture device 114 on object
112 and instructed camera 110 to capture an image of object 112,
camera computer 118 commands imaging capture device 114 via system
bus 116 to capture raw image data representing object 112. The captured
raw image data is transferred over system bus 116 to camera computer
118, which performs various image-processing functions on the image
data. System bus 116 also passes various status and control signals
between imaging capture device 114 and camera computer 118.
[0026] Referring now to FIG. 2, a block diagram of one embodiment
for imaging device 114 of FIG. 1 is shown. Imaging device 114 preferably
comprises a lens 220 having an iris (not shown), a filter 222, an
image sensor 224, a timing generator 226, an analog signal processor
(ASP) 228, an analog-to-digital (A/D) converter 230, an interface
232, and one or more motors 234 to adjust focus of lens 220.
[0027] Imaging capture device 114 captures an image of object 112
via reflected light impacting image sensor 224 along optical path
236. Image sensor 224, which is preferably a charged-coupled device
(CCD), responsively generates a set of raw image data in CCD format
representing the captured image 112. The raw image data is then
routed through ASP 228, A/D converter 230, and interface 232. Interface
232 has outputs for controlling ASP 228, motors 234 and timing generator
226. From interface 232, the raw image data passes over system bus
116 to camera computer 118.
[0028] Referring now to FIG. 3, a block diagram of one embodiment
for camera computer 118 of FIG. 1 is shown. System bus 116 provides
communication between imaging capture device 114, electrically-erasable
programmable read-only memory (EEPROM) 341, optional power manager
342, central processing unit (CPU) 344, dynamic random-access memory
(DRAM) 346, camera input/output (I/O) 348, non-volatile memory 350,
and buffers/connector 352. Removable memory 354 connects to system
bus 116 via buffers/connector 352. In alternate embodiments, camera
110 may also readily be implemented without removable memory 354
or buffers/connector 352.
[0029] Power manager 342 communicates with power supply 356 and
coordinates power management operations for camera 110. CPU 344
preferably includes a processor device for controlling the operation
of camera 110. In the preferred embodiment, CPU 344 is capable of
concurrently running multiple software routines to control the various
processes of camera 110 within a multi-threading environment. DRAM
346 is a contiguous block of dynamic memory, which may be selectively
allocated to various storage functions. LCD controller 390 accesses
DRAM 346 and transfers processed image data to LCD screen 302 for
display.
[0030] Camera I/O 348 is an interface device allowing communications
to and from camera computer 118. For example, camera I/O 348 permits
an external host computer (not shown) to connect to and communicate
with camera computer 118. Camera I/O 348 may also interface with
a plurality of buttons and/or dials 304, and an optional status
LCD 306, which, in addition to LCD screen 302, are the hardware
elements of the camera's user interface 308.
[0031] Non-volatile memory 350, which preferably comprises a conventional
read-only memory or flash memory, stores a set of computer-readable
program instructions to control the operation of camera 110. Removable
memory 354 serves as an additional image data storage area and is
preferably a non-volatile device, readily removable and replaceable
by a camera user via buffers/connector 352. Thus, a user who possesses
several removable memories 354 may replace a full removable memory
354 with an empty removable memory 354 to effectively expand the
picture-taking capacity of camera 110. In the preferred embodiment
of the present invention, removable memory 354 is preferably implemented
using a flash disk.
[0032] Power supply 356 provides operating power to the various
components of camera 110 via main power bus 362 and secondary power
bus 364. The main power bus 362 provides power to imaging capture
device 114, camera I/O 348, non-volatile memory 350 and removable
memory 354, while secondary power bus 364 provides power to power
manager 342, CPU 344 and DRAM 346.
[0033] Power supply 356 is connected to main batteries 358 and
also to backup batteries 360. Camera 110 user may also connect power
supply 356 to an optional external power source. During normal operation
of power supply 356, main batteries 358 provide operating power
to power supply 356 which then provides the operating power to camera
110 via both main power bus 362 and secondary power bus 364. During
a power failure mode where main batteries 358 have failed (i.e.,
when their output voltage has fallen below a minimum operational
voltage level), backup batteries 360 provide operating power to
power supply 356 which then provides operating power only to the
secondary power bus 364 of camera 110.
[0034] Referring now to FIG. 4, a rear elevation view of one embodiment
for camera 110 of FIG. 1 is shown. The FIG. 4 representation depicts
hardware components of user interface 308 of camera 110, showing
LCD screen 302, user interface 308, a four-way navigation control
button 409, an overlay button 412, a menu button 414, and a set
of programmable soft keys 416.
[0035] User interface 308 includes several operating modes for
supporting various camera functions. In the preferred embodiment,
operating modes may include capture mode, review mode, play mode,
and PC-connect mode. Within capture mode, menu options are available
to set-up the categories used during image capture. The user preferably
switches between the camera modes by selecting a mode dial (not
shown).
[0036] Referring now to FIG. 5, a diagram one embodiment for the
non-volatile memory 350 of FIG. 3 is shown. The FIG. 5 diagram includes
control application 500, toolbox 502, drivers 504, kernel 506, and
system configuration 508. Control application 500 comprises program
instructions for controlling and coordinating the various functions
of camera 110. Toolbox 502 contains selected function modules including
image processing backplane 510, image processing modules 512, menu
and dialog manager 514, and file formatter 516.
[0037] Image processing backplane 510 includes software routines
that coordinate the functioning and communication of various image
processing modules 512 and handle the data flow between the various
modules. Image processing modules 512 preferably include selectable
plug-in software routines that manipulate captured image data in
a variety of ways, depending on the particular modules selected.
Menu and dialog manager 514 includes software routines which provide
information for controlling access to camera control menus and camera
control menu items for access to features in camera 110. File formatter
516 includes software routines for creating an image file from the
processed image data.
[0038] Drivers 504 control various hardware devices within camera
110 (for example, motors 234). Kernel 506 provides basic underlying
services for the camera 110 operating system. System configuration
508 performs initial start-up routines for camera 110, including
the boot routine and initial system diagnostics.
[0039] Now referring to FIG. 6, a diagram of one embodiment for
dynamic random-access-memory (DRAM) 346 is shown. DRAM 346 includes
RAM disk 532, system area 534, analysis modules 540 and working
memory 530.
[0040] 1 In the preferred embodiment, RAM disk 532 is a memory
area used for storing raw and compressed image data and is organized
in a "sectored" format similar to that of conventional
hard disk drives. A conventional and standardized file system permits
external host computer systems, via I/O 348, to recognize and access
the data stored on RAM disk 532. System area 534 stores data regarding
system errors (e.g., why a system shutdown occurred) for use by
CPU 344 to restart computer 118.
[0041] Working memory 530 includes stacks, data structures and
variables used by CPU 344 while executing the software routines
used within camera computer 118. Working memory 530 also includes
input buffers 538 for initially storing sets of image data received
from imaging device 114 for image conversion, and frame buffers
536 for storing data to display on LCD screen 302.
[0042] In accordance with the present invention, analysis modules
540 preferably each include one or more software routines for automatically
analyzing and categorizing images. In the FIG. 6 embodiment, analysis
modules 540 may be loaded into RAM 346 from removable memory 354
or another external source. Analysis modules 540 further discussed
below in conjunction with FIGS. 7 through 10.
[0043] Referring now to FIG. 7, a diagram of one embodiment for
a single analysis module 540 of FIG. 6 is shown. Analysis module
540 includes text category list 610, combination logic 615, analysis
algorithms 630, and parametric control 635.
[0044] Text category list 610 is a listing of the various possible
image categories available for a given analysis module 540. Combination
logic 615 determines how to resolve the results of the image analysis
when multiple analysis algorithms 630 are utilized. Parametric control
635 is used to control settable parameters for analysis module 540.
For example, analysis module may be turned on/off, or sensitivity
settings for analysis module 540 may be controlled with parametric
control 635.
[0045] Analysis algorithms 630 are a series of software routines
ranging from analysis algorithm 1 (620) through analysis algorithm
n (625.) Analysis algorithms 630 are each designed to allow analysis
module 540 to access and analyze images at various stages in the
processing chain of camera 110, in order to gather information about
the image for later categorization.
[0046] Typically, each analysis algorithm 630 is designed to detect
at least one image category. For example, individual analysis algorithms
630 may be designed to detect a person or groups of people based
on characteristics like substantial amounts of flesh tones within
the image. Individual analysis algorithms 630 may likewise be designed
to detect nature scenes from characteristics like substantial green
content in the image combined with the relative lack of hard edges.
Similarly, categories like city images, water images or indoor images
may be detected by characteristic features contained in those images.
Once the last line of image data from a given image is processed,
analysis module 540 then preferably generates one or more category
tags that correspond to the particular image, and the generated
category tags are stored as part of the image file. A user of camera
110 may thus readily utilize the category tags to efficiently access
and sort images into selected categories.
[0047] Referring now to FIG. 8, a diagram of one embodiment for
an image file 835 is shown, in accordance with the present invention.
In the FIG. 8 embodiment, image file 835 includes a header 805,
image data 810, a screennail 815, a thumbnail 820, and image tags
825.
[0048] Header 805 preferably includes information that identifies
and describes the various contents of image file 835. Image data
810 contains actual captured image data. Image data 810 exists in
whichever format that is appropriate for the current location of
image file 835 within the image processing chain of camera 110.
Screennail 815 and thumbnail 820 are each different versions of
image data 810 that have varying degrees of reduced resolution for
a number of special viewing applications.
[0049] Image tags 825 includes various types of information that
correspond and relate to particular captured image data 810. Image
tags 825 are further discussed below in conjunction with FIG. 9.
[0050] Referring now to FIG. 9, a diagram of one embodiment for
the image tags of FIG. 8 is shown. In the FIG. 9 embodiment, image
tags 825 include capture information tags 710, user tags 715, product
tags 720, and category tags 735.
[0051] Capture information tags 710 preferably include various
types of information that correlate with the captured image data
810 (FIG. 8). For example, capture information tags 710 may indicate
focus setting, aperture setting, and other relevant information
that may be useful for effectively processing or analyzing the corresponding
image data 810. User tags 715 and product tags 720 typically contain
various other information that may be needed for use with camera
110.
[0052] Category tags 735 are each preferably generated by analysis
modules 540 after analysis modules 540 individually examine image
data 810 from image file 835, in accordance with the present invention.
Camera 110 may thus advantageously access and utilize category tags
735 to identify one or more categories to which a given set of image
data 810 may likely relate. As discussed above in conjunction with
FIG. 7, category tags 735 may correspond to a wide variety of possible
image categories. In the preferred embodiment, image tags 825 initially
contains sixteen empty locations to which various analysis modules
540 may write appropriate category tags 735 for automatically categorizing
the corresponding image data 810, in accordance with the present
invention.
[0053] Referring now to FIG. 10, a flowchart is shown for one embodiment
of method steps to automatically analyze and categorize images,
according to the present invention. FIG. 10 also details the operation
of a series of plug-in image processing modules 512 for processing
and formatting image data 810. However, in other embodiments of
camera 110, various other modules may readily be substituted or
added to those modules discussed in below conjunction with the FIG.
10 embodiment.
[0054] Initially, in step 910, camera 110 preferably captures a
selected image as CCD raw data, stores the raw data as image data
810 into image file 835, and then propagates image file 835 through
camera 110 for processing and formatting of the image data 810.
In step 920, an image processing module 512 preferably replaces
any defective pixels in image data 810, and also performs white
balance and color correction on image data 810.
[0055] Next, in step 925, another image processing module 512 preferably
performs interpolation (edge enhancement) on image data 810, and
then converts image data 810 into an intermediate format. In the
preferred embodiment, step 925 converts image data 810 into an RGB
(Red, Blue, Green) format.
[0056] In the FIG. 10 embodiment, following step 925, selected
analysis modules 540 may be plugged into an RGB insertion point
940 to advantageously analyze image data 810 at RGB transition point
930, in accordance with the present invention. One, some, or all
of the analysis modules 540 may analyze image data 810 at RGB transition
point 930. Preferably, analysis modules 540 are selected for optimal
compatibility and effectiveness with the current format of image
data 810 at RGB transition point 930. Once a particular analysis
module 540 analyzes the final line of image data 810, then that
analysis module 540 preferably generates any appropriate category
tags 735 and stores the generated category tags 735 into a blank
category tag location in image file 835. Then, camera 110 may subsequently
access the stored category tags 735 to automatically categorize
and utilize the individual stored images (which each correspond
to a separate image file 835).
[0057] Next, in step 945, another image processing module 512 preferably
performs gamma correction and color space conversion on image data
810. During step 945, the image processing module 512 also preferably
converts the color space format of image data 810. In the FIG. 10
embodiment, image data 810 is converted to YCC 444 (Luminance, Chrominance-red,
and Chrominance-blue) format.
[0058] In the FIG. 10 embodiment, following step 945, selected
analysis modules 540 may be plugged into a YCC insertion point 960
to analyze image data 810 at YCC transition point 950, in accordance
with the present invention. One, some, or all of the analysis modules
540 may analyze image data 810 at YCC transition point 950. As discussed
above, once a particular analysis module 540 analyzes the final
line of image data 810, then that analysis module 540 preferably
generates any appropriate category tags 735 and stores the generated
category tags 735 into a blank category tag location in image file
835 for subsequent use by camera 110 to automatically categorize
captured images.
[0059] This discussion of the FIG. 10 embodiment specifically refers
only RGB insertion point 940 and YCC insertion point 960. However,
in other embodiments of the present invention, analysis modules
540 may readily analyze image data 810 at any other time or insertion
point within camera 110. For example, in an alternate embodiment,
analysis modules 540 may readily be configured to examine image
data 810 at capture time, and to specifically recognize and identify
the capture of any image that matches one or more selectable parameters.
[0060] Furthermore, in another embodiment, analysis modules 540
may advantageously access image files 835 that have been processed
and stored onto removable memory 354. Analysis modules 540 may then
automatically categorize the image files 835 by analyzing image
data 810 and responsively generating corresponding category tags
735, in accordance with the present invention.
[0061] In step 965, an image processing module 512 preferably performs
a sharpening procedure on image data 810, and also may perform a
variety of other processing options. Then, in step 970, an image
processing module 512 preferably decimates image data 810. In the
preferred embodiment, the decimation process reduces image resolution
by decimating the YCC 444 image data to produce YCC 422 or YCC 411
image data.
[0062] In step 975, the image data 810 is preferably compressed
into a final image format (preferably JPEG.) Next, in step 980,
file formatter 516 preferably formats the compressed image file
835, and the resulting image file 835 is finally saved into removable
memory 354 in step 985. As discussed above, image file 835 thus
includes any appropriate category tags which camera 110 may then
subsequently automatically access to sort selected images, in accordance
with the present invention.
[0063] The invention has been explained above with reference to
a preferred embodiment. Other embodiments will be apparent to those
skilled in the art in light of this disclosure. For example, the
present invention may readily be implemented using configurations
other than those described in the preferred embodiment above. Additionally,
the present invention may effectively be used in conjunction with
systems other than the one described above as the preferred embodiment.
Therefore, these and other variations upon the preferred embodiments
are intended to be covered by the present invention, which is limited
only by the appended claims.
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