US6873743B2 — Method and apparatus for the automatic real-time …

Claim 1

Independent Claim 113 words

An automated method for detecting red-eye defects in a digital image comprising: (a) identifying and labeling an image segment that includes a potential red-eye defect in the image based on a red chrominance component and a luminance component of a color map; (b) eliminating a segment as a candidate for having a red-eye defect, said eliminating including testing said segment and a boundary region of said image surrounding said segment for a plurality of attributes to determine if each said attribute exceeds a pre-determined threshold value; and (c) recording a location, size and member pixels of a segment that survives said eliminating and is confirmed to have a red-eye defect of said image.

Claim 2

Dependent Claim 113 words

An automated method for detecting red-eye defects in a digital image comprising: (a) identifying and labeling an image segment that includes a potential red-eye defect in the image based on a red chrominance component and a luminance component of a color map; (b) eliminating a segment as a candidate for having a red-eye defect, said eliminating including testing said segment and a boundary region of said image surrounding said segment for a plurality of attributes to determine if each said attribute exceeds a pre-determined threshold value; and (c) recording a location, size and member pixels of a segment that survives said eliminating and is confirmed to have a red-eye defect of said image.

Claim 3

Dependent Claim 17 words

An automated method as recited in claim 1 wherein said attributes include the area of the segment.

Claim 4

Dependent Claim 18 words

An automated method as recited in claim 1 wherein said attributes include an elongation ratio of the segment.

Claim 5

Dependent Claim 18 words

An automated method as recited in claim 1 wherein said attributes include a compaction ratio of the segment.

Claim 6

Dependent Claim 33 words

An automated method as recited in claim 1 wherein said attributes of said bounding region include a number of pixels in the bounding region of the segment matching a color of human skin.

Claim 7

Dependent Claim 38 words

An automated method as recited in claim 1 wherein said attributes of said bounding region include a number of pixels in the bounding region of the segment matching a whitish color of a corneal region of an eye.

Claim 8

Dependent Claim 27 words

An automated method as recited in claim 1 wherein said attributes of said bounding region include an internal contrast ratio of a combined segment and bounding region.

Claim 9

Dependent Claim 58 words

An automated method as recited in claim 1 wherein said threshold values include an upper threshold value and a lower threshold value and said testing threshold values is modified to allow for both said upper and lower threshold value, for allowing for both a maximum and a minimum threshold value for some of said attributes of a segment.

Claim 10

Dependent Claim 41 words

An automated method as recited in claim 1 wherein said threshold values include a plurality of upper threshold values and a plurality of lower threshold values associated with said attributes, wherein said eliminating depends on which of said thresholds is exceeded.

Claim 11

Dependent Claim 29 words

An automated method as recited in claim 9 wherein said eliminating further includes testing for an additional characteristic, said characteristic being dependent on which of said thresholds is exceeded.

Claim 12

Dependent Claim 32 words

An automated method as recited in claim 1 wherein, within a predetermined range, the value of a particular attribute of a segment may directly determine said threshold value of subsequent test attributes.

Claim 13

Dependent Claim 25 words

An automated method as in claim 1 wherein said eliminating is based on a fuzzy relationship between two or more said attributes of said segment.

Claim 14

Dependent Claim 15 words

An automated method as recited in claim 1 further comprising correcting a confirmed red-eye defect.

Claim 15

Dependent Claim 99 words

An automated method as recited in claim 13 wherein said correcting the confirmed red-eye defect includes the steps of (a) creating a cumulative chrominance histogram of said confirmed red-eye defect of said image; (b) determining a threshold value for red colors; (c) clipping all red components of pixels in said confirmed red-eye defect which are larger than said threshold value; (d) maintaining all other luminance and chrominance values of said pixels as they are thus retaining the original color of said confirmed red-eye region; and (e) Repeating the above steps (a)-(d) for said each defect out of said defects.

Claim 16

Dependent Claim 33 words

An automated method for detecting a red-eye defect in a digital image as recited in claim 1 wherein said method is implemented in a digital camera as part of a post acquisition process.

Claim 17

Dependent Claim 45 words

An automated method for detecting a red-eye defect in a digital image as implemented in a digital camera as part of a post acquisition process as recited in claim 15 wherein a criteria for activating the said method is acquiring said image using a flash.

Claim 18

Dependent Claim 51 words

An automated method for detecting red-eye defects in a digital image as implemented in a digital camera as part of a post acquisition process as recited in claim 15 wherein a criteria for activating said method is a distance of a subject matter to the camera when said image is acquired.

Claim 19

Dependent Claim 72 words

An automated method for detecting red-eye defects in a digital image as implemented in a digital camera as part of a post acquisition process as recited in claim 15 further comprising the steps: (a) notifying a user of the existence of said red-eye defects prior to saving the image; and (b) providing the user with a choice wherein the user can take action to correct the red-eye prior to saving the image.

Claim 20

Dependent Claim 36 words

An automated method for detecting a red-eye defect in a digital image as recited in claim 1 wherein said method is implemented in high volume photographic printing machines as part of the printing process of images.

Claim 21

Dependent Claim 81 words

An automated method for detecting red-eye defects in a digital image as implemented in a high volume photographic printing machine as part of the printing process of images as recited in claim 19 further comprising the steps: (a) notifying an operator of said photographic printing machine of the existence of said red-eye defects prior to printing the image; and (b) providing the operator with a choice wherein the operator can take action to correct the red-eye prior to printing the image.

Claim 22

Dependent Claim 95 words

An automated method of correcting red-eye defects in detected red-eye regions in a digital image for each individual defect out of said red-eye defects in said detected regions comprising: (a) creating a cumulative chrominance histogram of said detected red-eye region of said image; (b) determining a threshold value for red colors; (c) clipping all red components of pixels in said detected red-eye region which are larger than a threshold value; and (d) maintaining all other luminance and chrominance values of said pixels as they are thus retaining an original color of said detected red-eye region.

Claim 23

Dependent Claim 95 words

An automated method of correcting red-eye defects in detected red-eye regions in a digital image for each individual defect out of said red-eye defects in said detected regions comprising: (a) creating a cumulative chrominance histogram of said detected red-eye region of said image; (b) determining a threshold value for red colors; (c) clipping all red components of pixels in said detected red-eye region which are larger than a threshold value; and (d) maintaining all other luminance and chrominance values of said pixels as they are thus retaining an original color of said detected red-eye region.

Claim 24

Dependent Claim 278 words

A user interactive red-eye detection system of digital images comprising: (a) apparatus for automatic detection of the existence of a red-eye region having a red-eye defect in an image including (i) first apparatus to segment and label a potential red-eye region in said image based on a red chrominance component and a luminance component of a color map; (ii) second apparatus to eliminate a segment which is considered a said potential red-eye region based on testing threshold values for a range of attributes of said segment and a region of the image immediately surrounding said segment, known as a bounding region; (iii) third apparatus to record a location, size and member pixels of a segment that is not eliminated by the second apparatus and is thus considered to be a potential red-eye region; (b) apparatus for indicating to a user that an area of said image has been designated as a potential red-eye region; (c) apparatus providing a user facility to choose to direct said system to correct said defect or choose to direct said system not to correct said defect; (d) apparatus for automatic correction of said defect including (i) first apparatus for creating a cumulative chrominance histogram of said detected red-eye region of said image; (ii) second apparatus for determining a threshold value for the red chrominance component for said red-eye region; (iii) third apparatus for clipping all red components of pixels in said detected red-eye region which are larger than said threshold values; and (iv) fourth apparatus for maintaining all other luminance and chrominance values of said pixels of said red-eye region as they are thus retaining the original colors of said detected red-eye region.

Claim 25

Dependent Claim 278 words

A user interactive red-eye detection system of digital images comprising: (a) apparatus for automatic detection of the existence of a red-eye region having a red-eye defect in an image including (i) first apparatus to segment and label a potential red-eye region in said image based on a red chrominance component and a luminance component of a color map; (ii) second apparatus to eliminate a segment which is considered a said potential red-eye region based on testing threshold values for a range of attributes of said segment and a region of the image immediately surrounding said segment, known as a bounding region; (iii) third apparatus to record a location, size and member pixels of a segment that is not eliminated by the second apparatus and is thus considered to be a potential red-eye region; (b) apparatus for indicating to a user that an area of said image has been designated as a potential red-eye region; (c) apparatus providing a user facility to choose to direct said system to correct said defect or choose to direct said system not to correct said defect; (d) apparatus for automatic correction of said defect including (i) first apparatus for creating a cumulative chrominance histogram of said detected red-eye region of said image; (ii) second apparatus for determining a threshold value for the red chrominance component for said red-eye region; (iii) third apparatus for clipping all red components of pixels in said detected red-eye region which are larger than said threshold values; and (iv) fourth apparatus for maintaining all other luminance and chrominance values of said pixels of said red-eye region as they are thus retaining the original colors of said detected red-eye region.

Claim 26

Dependent Claim 42 words

A user interactive red-eye detection system as recited in claim 22 wherein said apparatus for indicating to a user that an area of said image has been designated as a potential red-eye region provides a visual highlighting of said potential red-eye region.

Claim 27

Dependent Claim 37 words

A user interactive red-eye detection system as recited in claim 22 wherein said apparatus for indicating to a user that an area of said image has been designated as a potential red-eye region provides an audible signal.

Claim 28

Dependent Claim 22 words

A user interactive red-eye detection system as recited in claim 22 wherein said user is an operator of a digital printing machine.

Claim 29

Dependent Claim 23 words

A user interactive red-eye detection system as recited in claim 22 wherein said user is an operator of a computer image editing application.

Claim 30

Dependent Claim 33 words

A user interactive red-eye detection system as recited in claim 22 wherein said user is an operator of a digital camera wherein said digital image is an image captured by said digital camera.

Annuity Stage	Window Opens	Payment Deadline	Surcharge Period Until	Estimated Fee	Status
3.5 Years (Year 4)	2008-03-28	2008-09-27	2009-03-29	$2000.00	Window Closed / Lapsed
7.5 Years (Year 8)	2012-03-28	2012-09-27	2013-03-29	$3760.00	Window Closed / Lapsed
11.5 Years (Year 12)	2016-03-28	2016-09-27	2017-03-29	$7700.00	Window Closed / Lapsed

Method and apparatus for the automatic real-time detection and correction of red-eye defects in batches of digital images or in handheld appliances

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