Analyzing partial face regions for red-eye detection in acquired digital images

• US 8,254,674 B2
• Filed: 08/31/2009
• Issued: 08/28/2012
• Est. Priority Date: 10/28/2004
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: DigitalOptics Corporation Europe Limited (Adeia Inc.)
• Inventors: Zamfir, Adrian, Steinberg, Eran, Corcoran, Peter, Pososin, Alexei, Bigioi, Petronel, Nanu, Florin, Drimbarean, Alexandru, Petrescu, Stefan, Gangea, Mihnea, Capata, Adrian, Ciuc, Mihai
• Primary Examiner(s): Do, Anh Hong
• Application Number:
  US12/551,258
• Publication Number:
  US 20100054592A1
• Time in Patent Office: 1,093 Days
• Field of Search: 382/162, 382/167, 382/117, 382/159, 382/190, 382/165, 382/103, 382/118, 382/163, 348/222.1, 348/E5.024, 358/1.15, 358/1.9, 358/3.26, 358/515, 248/267
• US Class Current: 382/167
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30216 Redeye defect
• CPC Class Codes: G06T 5/77 Retouching; Inpainting; Scratch removal
• CPC Class Codes: G06T 5/94 based on local image properties, e.g. for local contrast enhancement
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: H04N 1/624 Red-eye correction control of camera based on recognised facial parts H04N23/611
• CPC Class Codes: H04N 23/56 provided with illuminating means
• CPC Class Codes: H04N 23/611 where the recognised objects include parts of the human body

Abstract

A method for red-eye detection in an acquired digital image includes acquiring a first image, and analyzing one or more partial face regions within the first image. One or more characteristics of the first image are determined. One or more corrective processes are identified including red eye correction that can be beneficially applied to the first image according to the one or more characteristics. The one or more corrective processes are applied to the first image.

Claims

1. A method for red-eye detection in an acquired digital image comprising:

using a processor;

acquiring a first image;

analyzing one or more partial face regions within the first image, including determining one or more characteristics of the first image;

identifying one or more corrective processes including red eye correction that can be beneficially applied to said first image according to said one or more characteristics; and

applying said one or more corrective processes to said first image.

2. The method of claim 1, further comprising detecting red-eye defects in a second acquired image based on the analyzing and identifying with regard to said first image.

3. The method of claim 2, wherein said applying comprises applying a chain of two or more red-eye filters to said first image;

and, prior to said detecting red eye defect in said second acquired image;

determining that said red-eye filter chain can be adapted for application to said second acquired image; and

then adapting said chain of two or more red-eye filters accordingly.

4. The method of claim 2, further comprising correcting a third acquired image based on analysis of the second acquired image.

5. The method of claim 4, wherein said first, second and third images comprise at least two different versions of a same image.

6. The method of claim 4, wherein at least one of said first and second images comprises a sub-sampled copy of said third image.

7. The method of claim 1, wherein at least one partial face region within the image is not among said one or more partial face regions identified within the image that are analyzed.

8. The method of claim 7, wherein said analysis is performed in part on a full resolution partial face region and in part on a subsample resolution of at least one different partial face region.

9. The method of claim 2, wherein said first and second images comprise versions of a same image.

10. The method of claim 2, wherein said first and second images comprises different images of substantially a same scene.

11. The method of claim 10, wherein said first image comprises a sub-sampled copy of an acquired image.

12. The method of claim 1, wherein the analyzing comprises recognizing one or more faces or types of faces, or both, within the first image.

13. The method of claim 1, wherein the red-eye correction process comprises:

pixel locating and segmentation;

shape analysis;

falsing analysis;

or pixel modification, or combinations thereof.

14. The method of claim 1, wherein the one or more corrective processes comprises a color space transformation.

15. One or more processor-readable media having digital code embedded therein for programming a processor to perform red-eye detection in an acquired digital image, wherein the digital code is configured to program the processor to analyze one or more partial face regions within a first image and to determine one or more characteristics of the first image;

and to identify one or more corrective processes including red eye correction that can be beneficially applied to said first image according to said one or more characteristics; and

to apply said one or more corrective processes to said first image.

16. The one or more processor-readable media of claim 15, wherein the digital code is further configured to program the processor to detect red-eye defects in a second acquired image based on analysis of said one or more partial face regions with the first image and identification of said one or more corrective processes with regard to said first image.

17. The one or more processor-readable media of claim 16, wherein said digital code is further configured to program the processor to apply a chain of two or more red-eye filters to said first image;

and, prior to detecting a red eye defect in a second acquired image, to determine that said red-eye filter chain can be adapted for application to said second acquired image; and

then to adapt said chain of two or more red-eye filters accordingly.

18. The one or more processor-readable media of claim 16, wherein the digital code is further configured to program the processor to correct a third acquired image based on analysis of the second acquired image.

19. The one or more processor-readable media of claim 18, wherein said first, second and third images comprise at least two different versions of a same image.

20. The one or more processor-readable media of claim 18, wherein at least one of said first and second images comprises a sub-sampled copy of said third image.

21. The one or more processor-readable media of claim 15, wherein at least one partial face region within the image is not among said one or more partial face regions identified within the image that are analyzed.

22. The one or more processor-readable media of claim 21, wherein said analysis is performed in part on a full resolution partial face region and in part on a subsample resolution of at least one different partial face region.

23. The one or more processor-readable media of claim 16, wherein said first and second images comprise versions of a same image.

24. The one or more processor-readable media of claim 16, wherein said first and second images comprises different images of approximately a same scene.

25. The one or more processor-readable media of claim 24, wherein said first image comprises a sub-sampled copy of an acquired image.

26. The one or more processor-readable media of claim 15, wherein the digital code is configured to program the processor to recognize one or more faces or types of faces, or both, within the first image.

27. The one or more processor-readable media of claim 15, wherein the red-eye correction process comprises:

pixel locating and segmentation;

shape analysis;

falsing analysis;

or pixel modification, or combinations thereof.

28. The one or more processor-readable media of claim 15, wherein the one or more corrective processes comprises a color space transformation.

29. A portable processor-based device having an image acquisition component including a lens and an image sensor for capturing digital images, and a processor programmed by digital code embedded in one or more processor-readable media to perform red-eye detection in an acquired digital image, wherein the digital code is configured to program the processor to acquire a first image;

to analyze one or more partial face regions within the first image, to determine one or more characteristics of the first image;

to identify one or more corrective processes including red eye correction that can be beneficially applied to said first image according to said one or more characteristics; and

to apply said one or more corrective processes to said first image.

30. The device of claim 29, wherein the digital code is configured to program the processor to detect red-eye defects in a second acquired image based on analysis of said one or more partial face regions within the first image and identification of said one or more corrective processes with regard to said first image.

31. The device of claim 30, wherein said digital code is configured to program the processor to analyze a chain of two or more red-eye filters to said first image;

and, prior to detecting red eye defect in said second acquired image, to determine that said red-eye filter chain can be adapted for application to said second acquired image; and

then to adapt said chain of two or more red-eye filters accordingly.

32. The device of claim 30, wherein the digital code is configured to program the processor to correct a third acquired image based on analysis of the second acquired image.

33. The device of claim 32, wherein said first, second and third images comprise at least two different versions of a same image.

34. The device of claim 33, wherein at least one of said first and second images comprises a sub-sampled copy of said third image.

35. The device of claim 29, wherein at least one partial face region within the image is not among said one or more partial face regions identified within the image that are analyzed.

36. The device of claim 35, wherein said analysis is performed in part on a full resolution partial face region and in part on a subsample resolution of at least one different partial face region.

37. The device of claim 30, wherein said first and second images comprise versions of a same image.

38. The device of claim 30, wherein said first and second images comprises different images of substantially a same scene.

39. The device of claim 38, wherein said first image comprises a sub-sampled copy of an acquired image.

40. The device of claim 29, wherein the digital code is configured to program the processor to recognize one or more faces or types of faces, or both, within the first image.

41. The device of claim 29, wherein the red-eye correction process comprises:

pixel locating and segmentation;

shape analysis;

falsing analysis;

or pixel modification, or combinations thereof.

42. The device of claim 29, wherein the one or more corrective processes comprises a color space transformation.