Detecting red eye filter and apparatus using meta-data

• US 7,630,006 B2
• Filed: 08/05/2003
• Issued: 12/08/2009
• Est. Priority Date: 10/09/1997
• Status: Expired due to Fees

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: FotoNation Ireland Limited (Adeia Inc.)
• Inventors: Steinberg, Eran, Prilutsky, Yury, Bigioi, Petronel, Corcoran, Peter, Pososin, Alexei, DeLuca, Michael J.
• Primary Examiner(s): Chan; Jason
• Assistant Examiner(s): Giles; Nicholas G
• Application Number:
  US10/635,862
• Publication Number:
  US 20040223063A1
• Time in Patent Office: 2,317 Days
• Field of Search: 348/241, 348/222.1, 348/370, 348/371, 382/117, 382/274, 382/275, 396/158, 396/166
• US Class Current: 348/241
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30041 Eye; Retina; Ophthalmic
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 2207/30216 Redeye defect
• CPC Class Codes: G06T 5/40 using histogram techniques
• 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 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction
• CPC Class Codes: H04N 1/6086 by scene illuminant, i.e. conditions at the time of picture capture, e.g. flash, optical filter used, evening, cloud, daylight, artificial lighting, white point measurement, colour temperature
• CPC Class Codes: H04N 1/62 Retouching, i.e. modification of isolated colours only or in isolated picture areas only
• 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 23/81 for suppressing or minimising disturbance in the image signal generation
• CPC Class Codes: H04N 25/60 Noise processing, e.g. detecting, correcting, reducing or removing noise

Abstract

A method of filtering a red-eye phenomenon from an acquired digital image including a multiplicity of pixels indicative of color, the pixels forming various shapes of the image, includes analyzing meta-data information, determining one or more regions within the digital image suspected as including red eye artifact, and determining, based at least in part on the meta-data analysis, whether the regions are actual red eye artifact. The meta-data information may include information describing conditions under which the image was acquired, captured and/or digitized, acquisition device-specific information, and/film information.

Claims

1. A method of filtering a red-eye phenomenon from an acquired digital image comprising a multiplicity of pixels indicative of color, the pixels forming various shapes within the image, the method comprising:

(a) analyzing meta-data information including image acquisition device-specific information including color transformation due to spectral response curve of sensor, or overall CCD size, or combinations thereof; and

(b) determining, based at least in part on said meta-data analysis, whether one or more regions within said digital image are suspected as including red eye artifact.

2. The method of claim 1, further comprising analyzing pixel information within one or more regions suspected as including red eye artifact based on said meta-data analysis, and determining whether any of said one or more suspected regions continue to be suspected as including red eye artifact based on said pixel analysis, said pixel analysis being performed after said meta-data analysis.

3. The method of claim 1, further comprising analyzing pixel information within said digital image, and determining whether said one or more regions are suspected as including red eye artifact based on said pixel analysis, and wherein said pixel analysis is performed after said meta-data analysis.

4. The method of claim 1, further comprising analyzing pixel information within said digital image, and determining whether one or more same or different regions are suspected as including red eye artifact based on said pixel analysis, said pixel analysis being performed independent of said meta-data analysis.

5. The method of claim 1, wherein the meta-data further comprises anthropometrical data.

6. The method of claim 1, wherein said filtering is executed at least partially within a portable image acquisition device having no photographic film.

7. The method of claim 1, wherein said filtering is executed at least in part as a post-processing operation on an external computation device.

8. The method of claim 7, wherein some or all of said meta-data analysis is performed on said image acquisition device.

9. The method of claim 8, further comprising marking certain regions determined to be suspected as including red eye artifact based on said analyzing, wherein said marking of certain regions facilitates correction during said post-processing operation on said external computation device.

10. The method of claim 7, wherein some of said meta-data analysis or said suspected region determining or a combination thereof is performed on said image acquisition device, and some of said meta-data analysis or said suspected region determining or a combination thereof is performed during said post-processing operation on said external computation device.

11. The method of claim 1, wherein a lens is used to capture the image, and wherein said meta-data information comprises focal length of the lens at the time of acquisition.

12. The method of claim 11, wherein said meta-data information further comprises focusing distance of the lens at time of acquisition.

13. The method of claim 11, wherein said meta-data information comprises effective sensor size.

14. The method of claim 13, wherein said actual red eye artifact is determined based on calculated expected size of said red eye artifact based on said meta-data information including said acquisition device-specific information.

15. The method of claim 14, wherein said calculated expected size of said red eye artifact is defined as a range with a density probability function, and wherein the range is calculated based on depth of field.

16. The method of claim 13, wherein said calculated expected size of said red eye artifact is defined as a range with a density probability function, and wherein the range is estimated.

17. The method of claim 13, wherein said calculated expected size of said red eye artifact is defined as a range with a density probability function, and wherein said meta-data comprises anthropometrical data, and wherein said range is determined by a statistical distribution of said anthropometrical data.

18. The method of claim 1, wherein said determining operation includes a probability determination process based upon a plurality of criteria.

19. The method of claim 1, further comprising:

(i) adjusting a pixel color within any of said regions wherein red eye artifact is determined; and

(ii) outputting image data to a printer.

20. The method of claim 19, wherein the pixel color is adjusted within the printer.

21. The method of claim 1, wherein said meta-data information comprises information describing conditions under which the image was acquired.

22. The method of claim 21, wherein said meta-data information comprises an indication of whether a flash was used when the image was acquired.

23. The method of claim 21, wherein said meta-data information comprises aperture at the time of the acquisition.

24. The method of claim 21, further comprising analyzing pixel information within one or more regions suspected as including red eye artifact based on said meta-data analysis, and determining whether any of said one or more suspected regions continue to be suspected as including red eye artifact based on said pixel analysis, said pixel analysis being performed after said meta-data analysis.

25. The method of claim 21, wherein the meta-data further comprises anthropometrical data.

26. The method of claim 21, wherein a lens is used to capture the image, and wherein said meta-data information comprises focal length of the lens at the time of acquisition.

27. The method of claim 26, wherein said meta-data information further comprises focusing distance of the lens at time of acquisition.

28. The method of claim 21, further comprising:

(i) adjusting a pixel color within any of said regions wherein red eye artifact is determined; and

(ii) outputting image data to a printer.

29. The method of claim 28, wherein the image is adjusted within the printer.

30. A method of filtering a red-eye phenomenon from an acquired digital image comprising a multiplicity of pixels indicative of color, the pixels forming various shapes within the image, the method comprising:

(a) analyzing meta-data information including image acquisition device-specific information including aperture, f-stop, color transformation due to spectral response curve of sensor, or overall CCD size, or combinations thereof; and

(b) determining, based at least in part on said meta-data analysis, whether one or more regions within said digital image are suspected as including red eye artifact, wherein said meta-data information comprises effective sensor width and length.

31. A method of filtering a red-eye phenomenon from an acquired digital image comprising a multiplicity of pixels indicative of color, the pixels forming various shapes within the image, the method comprising:

(a) analyzing meta-data information including image acquisition device-specific information including a spectral response curve of a sensor stored as a look-up table of an acquisition device with which the image was acquired; and

(b) determining, based at least in part on said meta-data analysis, whether one or more regions within said digital image are suspected as including red eye artifact.

32. The method of claim 31, wherein said meta-data information comprises a color transformation from raw sensor pixel values to saved image pixel values.

33. The method of claim 31, wherein said determining operation includes a probability determination process based upon a plurality of criteria.

34. The method of claim 31, wherein said meta-data information comprises acquisition device-specific information.

35. The method of claim 34, wherein said meta-data information comprises one or more conditions under which the image was acquired.

36. The method of claim 35, wherein said meta-data comprises a color transformation from raw sensor pixel values to saved image pixel values.

37. The method of claim 36, wherein color values of said pixels indicative of red eye color are calculated based on a spectral response of said red eye phenomenon.

38. The method of claim 37, wherein the spectral response of said red eye phenomenon is according to illumination by a spectral distribution of a camera flash unit.

39. The method of claim 38, wherein the spectral distribution of said camera flash unit is as recorded by said sensor of said acquisition device with which said image was acquired.

40. The method of claim 39, wherein said determining operation includes comparing pixels indicative of red eye color and a multiplicity of pixels forming various shapes.

41. The method of claim 40, wherein said pixels indicative of red eye color are calculated based on an inverse transformation of said color transformation from raw sensor pixel values to saved image pixel values.