Image analysis – Color image processing – Color correction
Reexamination Certificate
2004-09-15
2011-12-20
Ge, Yuzhen (Department: 2624)
Image analysis
Color image processing
Color correction
C382S190000
Reexamination Certificate
active
08081818
ABSTRACT:
Methods, systems, and computer program products used to locate a feature in an image, including identifying one or more candidate features in an image, where each candidate feature is a group of pixels in the image that satisfies a pattern-matching criterion. A best candidate feature is selected from the one or more candidate features, and a parameterized shape is fit to the image in the region of the best candidate feature to compute a feature shape corresponding to the best candidate feature. Particular implentations can include one or more of the following features. The candidate feature is a candidate pupil and the feature shape is an ellipse. Fitting the parameterizes shape to the mage includes applying an iterative process varying shape parameters. The parameterized shape encloses pixels in the image, and fitting the parameterized shape to compute an inner value, summing functions of values of pixels in the image outside of the parameterized shape to compute an outer value, and maximizing a difference between the inner value and the outer value.
REFERENCES:
patent: 5432863 (1995-07-01), Benati et al.
patent: 5583974 (1996-12-01), Winner et al.
patent: 6016354 (2000-01-01), Lin et al.
patent: 6144754 (2000-11-01), Okano et al.
patent: 6252976 (2001-06-01), Schildkraut et al.
patent: 6292574 (2001-09-01), Schildkraut et al.
patent: 6714665 (2004-03-01), Hanna et al.
patent: 6885760 (2005-04-01), Yamada et al.
patent: 6885761 (2005-04-01), Kage
patent: 6885766 (2005-04-01), Held et al.
patent: 7155058 (2006-12-01), Gaubatz et al.
patent: 1 223 550 (2002-07-01), None
patent: 1 271 394 (2003-01-01), None
Camus et al., “Reliable and fast eye finding in close-up images”, Proceedings 16thInternational Conference on Pattern Recognition, IEEE Computer Society, Aug. 11, 2002, pp. 389-394.
Zhu et al., “A fast automatic extraction algorithm of elliptic object groups from remote sensing images”, Pattern Recognition Letters, vol. 25, No. 13, Jul. 6, 2004, pp. 1471-1478.
Luo et al., “An efficient automatic redeye detection and correction algorithm”, Proceedings of the 17thInternational Conference on Pattern Recognition, IEEE, vol. 2, Aug. 23, 2004, pp. 883-886.
Kawaguchi et al., “Iris detection using intensity and edge information”, Pattern Recognition 36, (2003), pp. 549-562.
Kyungtae Hwang, “Pupil detection in photo ID”, Image Processing: Algorithms and Systems III, Proc. of SPIE-IS&T Electronic Imaging, SPIE vol. 5298, 2004, pp. 82-87.
Smolka et al., “Towards automatic redeye effect removal”, Pattern Recognition Letters 24 (2003) pp. 1767-1785.
Rizon et al., Automatic eye detetion using intensity and edge information, 2000 Tencon Proceedings, IEEE, vol. 2, Sep. 24, 2000, pp. 415-520.
Fukui et al., “Facial feature point extraction method based on combination of shape extraction and pattern matching”, Systems and Computers in Japan, vol. 29, No. 6, Jun. 15, 1998, pp. 49-58.
Sobottka et al., “A novel method for automatic face segmentation, facial feature extraction and tracking”, Image Communication 12 (1998) pp. 263-281.
Colorpilot, “Remove Red Eye—New Algorithm”, Retrieved from the Intenet http://www.colorpilot.com/redeye.html?adwords, Retrieved on Aug. 24, 2004, 2 pages.
Gaubatz, et al. “Automatic Red-Eye Detection and Correction”, IEEE 2002 International Conference on Image Processing, Rochester, New York, Sep. 22-25, 2002, pp. I-804 to I-807.
Jasc Software “Iris Color Change”, Retrieved from the Internet http://www/jasc.com/support/learn/tutorials/archive/paintshoppro/red-eye3.asp?pg=1, Retrieved on Aug. 24, 2004, 3 pages.
Jasc Software “Red-Eye Correction”, Retrieved from the Internet http://www/jasc.com/support/learn/tutorials/archive/paintshoppro/red-eye2.asp?pg=1, Retrieved on Aug. 24, 2004, 3 pages.
Jones et al., “Fast Multi-view Face Detection”, CVPR demo, Mitsubishi Electric Research Laboratories TR2003-96, http://www.merl.com (2003).
Schildkraut, et al. “A Fully Automatic Redeye Detection and Correction Algorithm”, IEEE 2002 International Conference on Image Processing, Rochester, New York, Sep. 22-25, 2002, pp. I-801 to I-803.
Schneiderman et al., “A Statistical Method for 3D Object Detection Applied to Faces and Cars”, Proc. CVPR 2000, 1:746-752.
Stoik,“Stoik RedEye Autofix”, Retrieved from the Internet http://www/stoik.com/stoik—red—eye/STOIK—RedEye—Autofix.htm, Retrieved on Aug. 24, 2004, 4 pages.
Ulichney, et al. “RedBot—a tool for improving red-eye correction”, IS&T/SID's Eleventh Color Imaging Conference, Scottsdale, Arizona, Nov. 4-7, 2003, 1 page.
Viola et al., “Robust Real-time Object Detection”, 2nd International Workshop on Statistical and Computational Theories of Vision—Modeling, Learning, Computing, and Sampling, Vancouver, CA (Jul. 13, 2001).
Wright, M.H., AT&T Bell Labs, “Direct Search Methods: Once Scorned, Now Respectable”, Proceedings of the 1995 Dundee Biennial Conference in Numerical Analysis, D.F. Grifiths and G.A. Watson, eds., Addison Wesley Longman, Harlow, UK, pp. 191-208 (1996).
Yang et al., “Detecting Faces in Images: A Survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1) (Jan. 2002).
Yuille, et al. “Feature Extraction from Faces Using Deformable Templates”, International Journal of Computer Vision, Springer Science+Business Media B.V., vol. 8, No. 2, Aug. 1992, pp. 99-111.
Adobe Systems Incorporated
Fish & Richardson P.C.
Ge Yuzhen
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