Automated detection and correction of eye color defects due to flash illumination
First Claim
Patent Images
1. A method of detecting for eye color defects of a subject in a digital image due to flash illumination, comprising the steps of:
- a) defining a spatial region within the digital image in which one or more eye color defects may exist, which region includes at least a portion of the subject'"'"'s head;
b) sampling pixels within such spatial region for their color content and comparing each such sample pixel with a plurality of threshold values which are representative of eye color defects to identify possible eye color defect pixels;
c) segmenting the identified possible eye color defective pixels into one or more spatially contiguous groups;
d) calculating a first score for each pixel of each segmented group and for each group based upon a plurality of features including group size, group shape, coloration, and brightness to identify eye color defect group candidates;
e) selecting a seed pixel based on its score from each identified eye color defect group candidate and determining all the neighboring pixels which are within a predetermined score range of their neighboring pixels and those pixels in a group which represent a significant pixel score transition so that the determined transitions identify the outer boundary of an eye color defect group candidate; and
f) calculating a second score for each pixel for each eye color defect group candidate based on a plurality of features including group size, group shape, coloration, and brightness to determine an actual eye color defect group.
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Abstract
A method of determining and correcting for eye color defects in an image due to flash illumination includes determining whether an eye color defect group candidate corresponds to a defective eye base based on group shape, coloration and brightness.
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Citations
20 Claims
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1. A method of detecting for eye color defects of a subject in a digital image due to flash illumination, comprising the steps of:
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a) defining a spatial region within the digital image in which one or more eye color defects may exist, which region includes at least a portion of the subject'"'"'s head; b) sampling pixels within such spatial region for their color content and comparing each such sample pixel with a plurality of threshold values which are representative of eye color defects to identify possible eye color defect pixels; c) segmenting the identified possible eye color defective pixels into one or more spatially contiguous groups; d) calculating a first score for each pixel of each segmented group and for each group based upon a plurality of features including group size, group shape, coloration, and brightness to identify eye color defect group candidates; e) selecting a seed pixel based on its score from each identified eye color defect group candidate and determining all the neighboring pixels which are within a predetermined score range of their neighboring pixels and those pixels in a group which represent a significant pixel score transition so that the determined transitions identify the outer boundary of an eye color defect group candidate; and f) calculating a second score for each pixel for each eye color defect group candidate based on a plurality of features including group size, group shape, coloration, and brightness to determine an actual eye color defect group. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A method of detecting for eye color defects of a subject in a digital image due to flash illumination, comprising the steps of:
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a) defining a spatial region within the digital image in which one or more eye color defects may exist, which region includes at least a portion of the subject'"'"'s head; b) sampling pixels within such spatial region for their color content and comparing each such sampled pixel with a plurality of threshold values which are representative of eye color defects to identify possible eye color defect pixels; c) segmenting the identified possible eye color defect pixels into one or more spatially contiguous groups; d) calculating a first score for each pixel of each segmented group and for each group based upon a plurality of features including group size, group shape, coloration, and brightness to identify eye color defect group candidates; e) selecting a seed pixel based on its score from each identified eye color defect group candidate and determining all the neighboring pixels which are within a predetermined score range of their neighboring pixels and those pixels in a group which represent a significant pixel score transition so that the determined transitions identify the outer boundary of an eye color defect group candidate; f) calculating a second score for each pixel for each eye color defect group candidate based on a plurality of features including group size, group shape, coloration, and brightness; g) selecting the best group score of an eye color defect group candidate and comparing it relative to a predetermined threshold group score to determine whether a first eye color defect group is present and identifying it as corresponding to the most likely eye; and h) determining whether a second actual eye color defect group is present based on whether the area of one of the color defect group candidate'"'"'s eye is within a predetermined threshold ratio of the area of the first actual eye color defect group corresponding to the most likely eye, and whether this group candidate is within a predetermined threshold angular subtense of the most likely eye along the predetermined horizontal axis of the subject'"'"'s head. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A method of detecting and correcting for eye color defects of a subject in a digital image due to flash illumination, comprising the steps of:
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a) defining a spatial region within the digital image in which one or more eye color defects may exist, which region includes at least a portion of the subject'"'"'s head; b) sampling pixels within such spatial region for their color content and comparing each such sampled pixel with a plurality of threshold values which are representative of eye color defects to identify possible eye color defect pixels; c) segmenting the identified possible eye color defect pixels into one or more spatially contiguous groups; d) calculating a first score for each pixel of each segmented group and for each group based upon a plurality of features including group size, group shape, coloration, and brightness to identify eye color defect group candidates; e) selecting a seed pixel based on its score from each identified eye color defect group candidate and determining all the neighboring pixels which are within a predetermined score range of their neighboring pixels and those pixels in a group which represent a significant pixel score transition so that the determined transitions identify the outer boundary of an eye color defect group candidate; f) calculating a second score for each pixel for each eye color defect group candidate based on a plurality of features including group size, group shape, coloration, and brightness; g) selecting the best group score of an eye color defect group candidate and comparing it relative to a predetermined threshold group score to determine whether a first eye color defect group is present and identifying it as corresponding to the most likely eye; and h) determining whether a second actual eye color defect group is present based on whether the area of one of the color defect group candidate'"'"'s eye is within a predetermined threshold ratio of the area of the first actual eye color defect group corresponding to the most likely eye, and whether this group candidate is within a predetermined threshold angular subtense of the most likely eye along the predetermined horizontal axis of the subject'"'"'s head; i) correcting the defective color in each eye color defect group by; (i) determining the correct resolution and whether each pixel at the corrected resolution is an eye color defect pixel; (ii) categorizing the eye color defect pixels at the corrected resolution into either body, border, or glint categories; and (iii) correcting the eye color defect pixels in the body, border, or glint categories. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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Specification