Foreground/background segmentation in digital images with differential exposure calculations

• US 20060039690A1
• Filed: 08/30/2005
• Published: 02/23/2006
• Est. Priority Date: 08/16/2004
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: FotoNation Vision Limited (Adeia Inc.)
• Inventors: Steinberg, Eran, Prilutsky, Yury, Corcoran, Peter, Blgiol, Petronel
• Granted Patent: US 7,606,417 B2
• Time in Patent Office: Days
• US Class Current: 396/155
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10152 Varying illumination
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 2207/30216 Redeye defect
• CPC Class Codes: G06T 5/77 Retouching; Inpainting; Scratch removal
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/174 involving the use of two or more images
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/40 Analysis of texture depth or shape recovery from texture G06T7/529
• CPC Class Codes: G06V 10/28 Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction
• CPC Class Codes: H04N 1/624 Red-eye correction control of camera based on recognised facial parts H04N23/611
• CPC Class Codes: H04N 23/74 by influencing the scene brightness using illuminating means
• CPC Class Codes: H04N 23/80 Camera processing pipelines; Components thereof

Abstract

A digital segmentation method and apparatus determines foreground and/or background within at least one portion of a captured image. The determining includes comparing a captured image to a pre-captured or post captured reference image of nominally the same scene. One of the images is taken with flash and the other without. The system can be implemented as part of a digital camera acquisition chain having effective computation complexity.

Claims

1. A digital image acquisition system having no photographic film, comprising:

(a) an apparatus for capturing digital images,

(b) a flash unit for providing illumination during image capture, and

(c) a segmentation tool for determining one or more regions that are indicative of a foreground region, or of a background region, or of a background region and a foreground region, within at least one portion of a captured image,

(d) wherein said determining comprises comparing said captured image and a reference image of nominally the same scene, and

(e) wherein one of said captured and reference images being taken with flash and the other being taken without flash.

2. A system according to claim 1, wherein the captured and reference images have different pixel resolutions, and wherein the system further comprises a pixel matching tool which is operative prior to application of the segmentation tool for matching the pixel resolutions of the captured and reference images at least in respect of said at least one portion.

3. A system according to claim 2, wherein said pixel matching tool utilizes up-sampling of the image of lower resolution or sub-sampling of the image of higher resolution, or both.

4. A system according to claim 1, further comprising an alignment tool which is operative prior to application of the segmentation tool for aligning said regions of said captured and reference images at least in respect of said at least one portion.

5. A system according to claims 1, further comprising an exposure equalizer for substantially equalizing an overall level of exposure of said regions or all of said captured and reference images at least in respect of said at least one portion.

6. A system according to claim 5, wherein the substantially equalising of the overall level of exposure of said regions or all of said captured and reference image comprises simulating an ambient exposure of the captured image on the reference image.

7. A system according to claim 6, wherein the simulating of the ambient exposure of the captured image on the reference image comprises digitally simulating a one or a combination of aperture, acquisition speed, color transformations and gain of the captured image on the reference image.

8. A system according to claims 6, wherein the simulating of the ambient exposure of the captured image comprises individual, non-uniform manipulating of individual regions or color channels or combinations thereof.

9. A system according to any one of claims 5, wherein the substantially equalising of the overall level of exposure of said captured and reference image comprises setting an ambient exposure of the reference image to match a calculated exposure of the captured image.

10. A system according to claim 5, wherein at least in respect of said at least one portion, the segmentation tool determines corresponding pixels in the captured and reference images whose values differ by less than a predetermined threshold, and designates segments of the captured image bounded by said determined pixels as foreground or background by comparing pixel values in a segment with pixel values in a corresponding segment of the reference image.

11. A system according to claim 5, wherein at least in respect of said at least one portion, the segmentation tool determines upper and lower thresholds based on a comparison of the overall level of exposure of the captured and reference images and designates pixels of the captured image as foreground or background according to whether their values are greater than the upper threshold or less than the lower threshold.

12. A system according to claim 5, wherein at least in respect of said at least one portion, the segmentation tool designates one or more segments of the captured image as foreground or background by comparing pixel values in the captured and reference images.

13. A system according to claim 5, wherein the reference image comprises a preview image having a lower pixel resolution than the captured image, and the captured image comprises the image taken with flash.

14. A system according to claim 1, further comprising a face detection module.

15. A system according to claim 1, further comprising a red-eye detection filter or a red eye correction filter or both, for selective application to the foreground region.

16. A system according to claim 15, further comprising a probability module for changing a probability of a redeye candidate region being an actual redeye region according to whether the candidate appears in the foreground or background of the captured image.

17. A system according to claim 1, further comprising a depth of focus module for reducing a perceived depth of focus according to whether a candidate region appears in the foreground or background of the captured image.

18. A system according to claim 1, wherein the reference image comprises a preview image.

19. A system according to claim 1, wherein the reference image comprises an image captured chronologically after said captured image.

20. A system according to claim 1, wherein the reference image comprises a combination of multiple reference-images.

21. A system according to claim 1, wherein said digital image acquisition system comprises a digital camera.

22. A system according to claims 1, wherein said digital image acquisition system comprises a combination of a digital camera and an external processing device.

23. A system as claimed in claim 22, wherein said segmentation tool is located within said external processing device.

24. A system according to claims 1, wherein said digital image acquisition system comprises a batch processing system including a digital printing device

25. A system according to claims 1, wherein said digital image acquisition system comprises a batch processing system including a server computer.

26. A digital segmentation tool for determining one or more regions that are indicative of a foreground region, or of a background region, or of a background region and a foreground region, within at least one portion of a captured image, wherein said determining comprises comparing said captured image and a reference image of nominally the same scene, and wherein one of said captured and reference images being taken with flash and the other being taken without flash.

27. A segmentation tool according to claim 26, wherein the captured and reference images have different pixel resolutions, and wherein the segmentation tool operates in conjunction with a pixel matching tool which is operative prior to application of the segmentation tool for matching the pixel resolutions of the captured and reference images at least in respect of said at least one portion.

28. A segmentation tool according to claim 27, wherein said pixel matching tool utilizes up-sampling of the image of lower resolution or sub-sampling of the image of higher resolution, or both.

29. A segmentation tool according to claim 26, wherein the segmentation tool operates in conjunction with an alignment tool which is operative prior to application of the segmentation tool for aligning said captured and reference images at least in respect of said at least one portion.

30. A segmentation tool according to claims 26, wherein said segmentation tool operates in conjunction with an exposure equalizer for substantially equalizing an overall level of exposure of said captured and reference images at least in respect of said at least one portion.

31. A segmentation tool according to claim 26, wherein said segmentation tool operates in conjunction with a face detection module or a red-eye filter, or both, for selective application to the foreground region.

32. A segmentation tool according to claim 31, wherein said segmentation tool further operates in conjunction with a probability module for changing a probability of a redeye candidate region being an actual redeye region according to whether the candidate appears in the foreground or background of the captured image.

33. A segmentation tool according to claim 31, wherein said segmentation tool further operates in conjunction with a depth of focus module for reducing a perceived depth of focus according to whether a candidate region appears in the foreground or background of the captured image.

34. A segmentation tool according to claim 31, wherein said segmentation tool further operates in conjunction with a blurring module for blurring said regions indicative of background of the captured image.

35. A segmentation tool according to claim 26, wherein the reference image comprises a preview image.

36. A segmentation tool according to claim 26, wherein the reference image comprises an image captured chronologically after said captured image.

37. A segmentation tool according to claim 26, wherein the reference image comprises a combination of multiple reference-images.