US6792134B2
Expired / Lapsed
US
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Multi-mode digital image processing method for detecting eyes
Assignee: Monument Peak Ventures LLC
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Filing: 2000-12-19
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Granted: 2004-09-14
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Expires: 2020-12-19
Abstract
Abstract The present invention comprises a digital image processing method for detecting human eyes in a digital image. This method comprises the steps of: detecting iris pixels in the image; clustering the iris pixels, and selecting at least one of the following methods to identify eye positions: applying geometric reasoning to detect eye positions using the iris pixel clusters; applying a summation of squared difference method using the iris pixel clusters to detect eye positions; and applying a summation of squared difference method to detect eye positions from the pixels in the image. The method applied is selected on the basis of the number of iris pixel clusters. In another embodiment, the present invention also comprises a computer program product.
Inventors
- 👤 Shoupu Chen
- 👤 Lawrence A. Ray
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 10:55
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/70; G06T7/73; G06T7/74; G06T7/90; G06V; G06V40/00; G06V40/10; G06V40/18; G06V40/19; G06T2207/00; G06T2207/30; G06T2207/30216
Claims Analysis
Total Claims: 45
Claim 1
Independent Claim
110 words
A digital image processing method for detecting human eyes in a digital image, comprising the steps of: detecting iris pixels; clustering the iris pixels; determining the number of iris pixel clusters; selecting at least one of the following methods to identify eye positions in an image: i) applying geometric reasoning to detect eye positions using the iris pixel clusters; ii) applying a summation of squared difference to detect eye positions based the iris color pixel clusters; iii) applying a summation of squared difference method to detect eye positions from the pixels in the image; wherein the applying step is selected on the basis of the number of iris pixel clusters.
Claim 2
Dependent Claim
110 words
A digital image processing method for detecting human eyes in a digital image, comprising the steps of: detecting iris pixels; clustering the iris pixels; determining the number of iris pixel clusters; selecting at least one of the following methods to identify eye positions in an image: i) applying geometric reasoning to detect eye positions using the iris pixel clusters; ii) applying a summation of squared difference to detect eye positions based the iris color pixel clusters; iii) applying a summation of squared difference method to detect eye positions from the pixels in the image; wherein the applying step is selected on the basis of the number of iris pixel clusters.
Claim 3
Dependent Claim
21 words
The method of claim 1 , wherein applying step iii) is selected when less than two iris pixel clusters are detected.
Claim 4
Dependent Claim
103 words
The method claimed in claim 2 , wherein the step of applying a summation of squared difference method to detect eye positions from the pixels in the image comprises the steps of: dividing the image pixels into left-half pixels and right-half pixels; locating the most likely left eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the left-half pixels; and locating the most likely right eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the right-half pixels.
Claim 5
Dependent Claim
33 words
The method of claim 3 further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 6
Dependent Claim
33 words
The method of claim 3 further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 7
Dependent Claim
21 words
The method of claim 1 , wherein applying step i) is selected when at least two iris pixel clusters are detected.
Claim 8
Dependent Claim
32 words
The method of claim 6 , wherein method i) is first applied and method ii) is subsequently applied in the event that method i) does not detect at least two eye positions.
Claim 9
Dependent Claim
21 words
The method of claim 7 , wherein method ii) does not detect eye positions and wherein method iii) is then applied.
Claim 10
Dependent Claim
103 words
The method claimed in claim 8 , wherein the step of applying a summation of squared difference method to detect eye positions from the pixels in the image comprises the steps of: dividing the image pixels into left-half pixels and right-half pixels; locating the most likely left eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the left-half pixels; and locating the most likely right eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the right-half pixels.
Claim 11
Dependent Claim
71 words
The computer program product of claim 9 , wherein the step of applying geometric reasoning using the detected iris color pixels comprises the steps of: finding the center of each iris pixel cluster; dividing the iris pixel clusters into left-half iris pixel clusters and right-half iris pixel clusters; and detecting a pair of eyes based on the geometric relationship between the left-half iris pixel clusters and the right-half iris pixel clusters.
Claim 12
Dependent Claim
151 words
The method of claim 7 , wherein the step of applying the summation squared difference method to detect eye positions based upon the iris pixel clusters, comprises the steps of: finding the center of each iris pixel cluster; defining a window of pixels surrounding each of the centers of the iris pixel clusters in the image; dividing the iris pixel clusters into left-half pixel clusters and right-half iris pixel clusters; locating the most likely left eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a left-half iris pixel cluster; and locating the most likely right eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a right-half iris pixel cluster.
Claim 13
Dependent Claim
57 words
The method of claim 11 further comprising the steps of detecting a skin color region in the image, and dividing the skin color region into a left-half region and right-half region wherein the iris pixel clusters are divided into left-half iris pixel clusters and right-half iris pixel clusters based upon the region in which they are located.
Claim 14
Independent Claim
60 words
The method of claims 6 , wherein the step of applying geometric reasoning using the detected iris color pixels comprises the steps of: finding the center of each iris pixel cluster; dividing the iris pixel clusters into left-half pixel clusters and right-half pixel clusters; and detecting a pair of eyes based on the geometric relationship between the iris pixel clusters.
Claim 15
Dependent Claim
60 words
The method of claim 1 , wherein the step of applying geometric reasoning using the detected iris color pixels comprises the steps of: finding the center of each iris pixel cluster; dividing the iris pixel clusters into left-half pixel clusters and right-half pixel clusters; and detecting a pair of eyes based on the geometric relationship between the iris pixel clusters.
Claim 16
Dependent Claim
151 words
The method of claim 1 , wherein the step of applying the summation squared difference method to detect eye positions based upon the iris pixel clusters, comprises the steps of: finding the center of each iris pixel cluster; defining a window of pixels surrounding each of the centers of the iris pixel clusters in the image; dividing the iris pixel clusters into left-half pixel clusters and right-half iris pixel clusters; locating the most likely left eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a left-half iris pixel cluster; and locating the most likely right eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a right-half iris pixel cluster.
Claim 17
Dependent Claim
57 words
The method of claim 15 further comprising the steps of detecting a skin color region in the image, and dividing the skin color region into a left-half region and right-half region wherein the iris pixel clusters are divided into left-half iris pixel clusters and right-half iris pixel clusters based upon the region in which they are located.
Claim 18
Dependent Claim
102 words
The method of claim 1 , wherein the step of applying a summation of squared difference method to detect eye positions from the pixels in the image comprises the steps of: dividing the image pixels into left-half pixels and right-half pixels; locating the most likely left eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the left-half pixels; and locating the most likely right eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the right-half pixels.
Claim 19
Dependent Claim
34 words
The method of claim 17 , further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 20
Dependent Claim
32 words
The method of claim 1 further comprising the step of validating iris pixel clusters, wherein the selection of the method to be applied is made based upon the number of valid clusters.
Claim 21
Dependent Claim
119 words
A computer program product for detecting human eyes in a digital image, the computer program product comprising a computer readable storage medium having a computer program stored thereon for performing the step of: detecting iris pixels; clustering the iris pixels; selecting at least one of the following methods to identify eye positions in the image: i) applying geometric reasoning to detect eye positions using the iris pixel clusters; ii) applying a summation of squared difference method to detect eye positions based upon the iris pixel clusters; and iii) applying a summation of squared difference method using non-iris pixels to detect eye positions; wherein the method applied is selected on the basis of the number of valid iris pixel clusters.
Claim 22
Dependent Claim
119 words
A computer program product for detecting human eyes in a digital image, the computer program product comprising a computer readable storage medium having a computer program stored thereon for performing the step of: detecting iris pixels; clustering the iris pixels; selecting at least one of the following methods to identify eye positions in the image: i) applying geometric reasoning to detect eye positions using the iris pixel clusters; ii) applying a summation of squared difference method to detect eye positions based upon the iris pixel clusters; and iii) applying a summation of squared difference method using non-iris pixels to detect eye positions; wherein the method applied is selected on the basis of the number of valid iris pixel clusters.
Claim 23
Dependent Claim
25 words
The computer program product of claim 20 , wherein less than two valid iris pixel clusters are detected and wherein detection method iii) is applied.
Claim 24
Dependent Claim
24 words
The computer program product of claim 20 , wherein at least two valid iris pixel clusters are detected and wherein method i) is applied.
Claim 25
Dependent Claim
25 words
The computer program product of claim 22 , wherein method i) does not detect eyes and wherein method ii) is then applied to detect eyes.
Claim 26
Dependent Claim
22 words
The computer program product of claim 23 , wherein method ii) does not detect eyes and wherein method iii) is then applied.
Claim 27
Dependent Claim
148 words
The computer program product of claim 23 , wherein the step of applying the summation squared method to detect eye positions based upon the iris pixel clusters, comprises the steps of: finding the center of each cluster; defining a window of pixels surrounding each of the centers of the pixel clusters in the image; dividing the iris pixel clusters into left-half pixel clusters and right-half pixel clusters; locating the most likely left eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the pixels in each of the windows surrounding a left-half iris pixel cluster; and locating the most likely right eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a right-half iris pixel cluster.
Claim 28
Dependent Claim
60 words
The computer program product of claim 25 further comprising the steps of detecting a skin color region in the image, and dividing the skin color region into a left-half region and a right-half region wherein the iris pixel clusters are divided into left-half iris pixel clusters and right-half iris pixel clusters based upon the region in which they are located.
Claim 29
Dependent Claim
71 words
The computer program product of claim 20 , wherein the step of applying geometric reasoning using the detected iris color pixels comprises the steps of: finding the center of each iris pixel cluster; dividing the iris pixel clusters into left-half iris pixel clusters and right-half iris pixel clusters; and detecting a pair of eyes based on the geometric relationship between the left-half iris pixel clusters and the right-half iris pixel clusters.
Claim 30
Dependent Claim
117 words
The computer program product of claim 27 wherein the step of detecting iris color pixels using a Bayes model comprises measuring the red intensity of the pixels in the skin color region; determining the probability that each pixel is an iris based upon the red intensity of the pixel; determining the probability that each pixel is not an iris based upon the red intensity of the pixel; and applying the Bayes model to the probability that the pixel is an iris, the probability that the pixel is not an iris, the probability of the occurrence of an iris in the skin colored region and probability of the occurrence of a non-iris pixel in the skin colored region.
Claim 31
Dependent Claim
36 words
The computer program product of claim 28 , further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 32
Dependent Claim
117 words
The computer program product of claim 27 wherein the step of detecting iris color pixels using a Bayes model comprises measuring the red intensity of the pixels in the skin color region; determining the probability that each pixel is an iris based upon the red intensity of the pixel; determining the probability that each pixel is not an iris based upon the red intensity of the pixel; and applying the Bayes model to the probability that the pixel is an iris, the probability that the pixel is not an iris, the probability of the occurrence of an iris in the skin colored region and probability of the occurrence of a non-iris pixel in the skin colored region.
Claim 33
Dependent Claim
36 words
The computer program product of claim 30 , further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 34
Dependent Claim
147 words
The computer program product of claim 20 , wherein the step of applying the summation squared method to detect eye positions based upon the iris pixel clusters, comprises the steps of: finding the center of each cluster; defining a window of pixels surrounding each of centers of the pixel clusters in the image; dividing the iris pixel clusters into left-half pixel clusters and right-half pixel clusters; locating the most likely left eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the pixels in each of the windows surrounding a left-half iris pixel cluster; and locating the most likely right eye position based on the summation of squared difference between an average eye and patches of the image centered at each of the pixels in each of the windows surrounding a right-half iris pixel cluster.
Claim 35
Dependent Claim
60 words
The computer program product of claim 32 further comprising the steps of detecting a skin color region in the image, and dividing the skin color region into a left-half region and a right-half region wherein the iris pixel clusters are divided into left-half iris pixel clusters and right-half iris pixel clusters based upon the region in which they are located.
Claim 36
Dependent Claim
101 words
The computer program product claimed in claim 20 wherein the step of applying a summation of squared difference method using image pixels to detect eye positions comprises the steps of: dividing the pixels in the image into left-half pixels and right-half pixels; locating the most likely left-eye position based on the summation of squared difference between an average eye and patch of the image centered at each of left-half pixels; and locating the most likely right eye position based on the summation of squared difference between an average eye and patch of the image centered at each of the right-half pixels.
Claim 37
Dependent Claim
36 words
The computer program product of claim 34 , further comprising detecting a skin color region in the image, wherein the summation of the squared difference method is only applied to pixels within the skin color region.
Claim 38
Dependent Claim
77 words
A digital image processing method for detecting human eyes comprising the steps of: detecting iris pixels; clustering iris pixels; determining the number of iris pixel clusters; selecting a method for detecting eye positions based upon the number of iris pixel clusters; and using the selected method to detect eye positions wherein the step of selecting a method for detecting eye positions based upon the number of iris pixel clusters comprises selecting a series of eye detection steps.
Claim 39
Dependent Claim
77 words
A digital image processing method for detecting human eyes comprising the steps of: detecting iris pixels; clustering iris pixels; determining the number of iris pixel clusters; selecting a method for detecting eye positions based upon the number of iris pixel clusters; and using the selected method to detect eye positions wherein the step of selecting a method for detecting eye positions based upon the number of iris pixel clusters comprises selecting a series of eye detection steps.
Claim 40
Dependent Claim
42 words
The digital image processing method of claim 36 , wherein the step of selecting a method for detecting eye positions based upon the number of iris pixel clusters comprises selecting a series of eye detection steps to be executed in sequential fashion.
Claim 41
Dependent Claim
35 words
The digital image processing method of claim 37 , wherein each eye detection step in the series of eye detection steps is used only where each of the preceding steps has not detected eye positions.
Claim 42
Dependent Claim
38 words
The digital image processing method of claim 36 , wherein the step of selecting a method for detecting eye positions is based upon the number of iris pixel clusters and the size of the image to be processed.
Claim 43
Dependent Claim
37 words
The digital image processing method of claim 36 , wherein the step of selecting a method for detecting eye positions is based upon the number of iris pixel clusters and the time required to execute each method.
Claim 44
Dependent Claim
37 words
The digital image processing method of claim 36 , wherein the step of selecting a method for detecting eye positions is based upon the number of iris pixel clusters and the computational efficiency of the method selected.
Claim 45
Dependent Claim
37 words
The digital image processing method of claim 36 , wherein the step of selecting a method for detecting eye positions is based upon the number of iris pixel clusters and probability that each method will detect eyes.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2007-09-14 | 2008-03-15 | 2008-09-14 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2011-09-14 | 2012-03-15 | 2012-09-14 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2015-09-14 | 2016-03-15 | 2016-09-14 | $7700.00 | Window Closed / Lapsed |