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EP1199672A2
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Red-eye detection method
Assignee: Xerox Corp
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Filing: 2001-10-09
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Granted: —
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Expires: 2021-10-09
Abstract
Abstract A red-eye detection method includes receiving digital image data that defines an image. The digital image data are processed to identify all regions of the image that include a specular reflection. Image regions deemed to include a specular reflection are processed further, according to conventional techniques, to determine the presence or absence of red-eye. Specular reflections are identified according to luminace-chrominance characteristics, geometric (e.g., size/shape) characteristics, and/or luminance gradient characteristics.
Inventors
- 👤 Reiner Eschbach
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-09 14:49
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/10; G06T7/11; G06T7/90; G06V; G06V40/00; G06V40/10; G06V40/18; G06V40/193; H; H04; H04N; H04N1/00; H04N1/46; H04N1/56; H04N1/60; H04N1/62; H04N1/624; G06T2207/00; G06T2207/30; G06T2207/30216
Claims Analysis
Total Claims: 10
Claim 1
Independent Claim
54 words
A digital image processing method for identifying potential red-eye
regions of a digital image, said method comprising: receiving a digital image defined by a plurality of pixels; locating regions of interest within said digital image that include pixels
that represent a specular reflection; and, identifying each region of interest as a potential red-eye region.
Claim 2
Dependent Claim
30 words
The digital image processing method as set forth in claim 1,
wherein said step of locating regions of interest comprises examining luminance-chrominance
data for each pixel of said digital image.
Claim 3
Dependent Claim
34 words
The digital image processing method as set forth in claim 2, further
comprising, before said step of examining luminance-chrominance data,
converting each of said pixels of said digital image to a luminance-chrominance
color space.
Claim 4
Dependent Claim
111 words
The digital image processing method as set forth in claim 2,
wherein said step of locating regions of interest in said digital image comprises: identifying a group of adjacent pixels of said digital image as a potential
specular reflection if said group of adjacent pixels comprises pixels having
luminance-chrominance characteristics of a specular reflection; for each identified potential specular reflection, determining at least one
geometric attribute of said potential specular reflection; comparing the at least one geometric attribute of said potential specular
reflection to a desired geometric attribute; and, identifying said potential specular reflection as a specular reflection if said
at least one geometric attribute conforms to said desired geometric attribute.
Claim 5
Dependent Claim
34 words
The digital image processing method of claim 4, wherein the at
least one geometric attribute of the potential specular reflection is at least one of
a size and shape of said potential specular reflection.
Claim 6
Dependent Claim
76 words
The digital image processing method as set forth in claim 4, further
comprising, for each potential specular reflection: determining a brightness gradient of said potential specular reflection; comparing said brightness gradient of said potential specular reflection to
a select brightness gradient threshold; and, identifying said potential specular reflection as a specular reflection if said
at least one geometric attribute conforms to said desired geometric attribute and
said brightness gradient is greater than said brightness gradient threshold.
Claim 7
Independent Claim
49 words
A method for detecting red-eye in a digital image, said method
comprising: receiving digital image data defining a digital image; identifying regions of interest in said digital image that include data that
represent a specular reflection; examining the data in each of said regions of interest to detect red-eye.
Claim 8
Dependent Claim
64 words
The red-eye detection method as set forth in claim 7, wherein said
step of identifying regions of interest comprises, for each region of an image: identifying said region as including a specular reflection if said region
includes a sub-region defined by at least one preset geometric attribute, a
luminance above a select luminance threshold, and a luminance gradient above
a select luminance gradient threshold.
Claim 9
Dependent Claim
30 words
The red-eye detection method as set forth in claim 8, wherein said
at least one preset geometric attribute comprises at least one of a preset size
and a preset shape.
Claim 10
Independent Claim
55 words
A method of detecting red-eye in a digital image, said method
comprising: receiving a digital image; identifying all regions of said digital image that include a specular
reflection; for each region of an image including a specular reflection, determining if
said region includes red-eye based upon a color of said region adjacent said
specular reflection.
References Cited (Backward Citations)
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