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Evolving Color Constancy Marc Ebner Universit ä t W ü rzburg, Germany Pattern Recognition Letters 27 ( 2006 ) 1220-1229 Elsevier
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Algorithms for color constancy Gamut – constraint methods Perspective color constancy Color by correlation The gray world assumption Recovery of basis function coefficients Mechanisms of light adaptation coupled with movements Neural networks Comprehensive color normalization Committee – based methods Algorithms based on the dichromatic color model Computation of intrinsic images
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PE ( Articial Retina ) PE : a rectangular grid of processing elements Better than neural nets, quite complicated.
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Processing elements 1 PE for 1 image pixel 3 layers of PEs carrying out results on the 3 image bands red, green, and blue. : Estimate of the illuminant ( color of input pixel ) The data from other neighboring PEs Initially, ( : pixel value )
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Conclusion Only the current color channel ( band ) is used. Average data from neighboring elements.
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Parallel algorithm The gray world assumption The reflectance, : distributed over the interval [0,1] From PE, N : the number of image pixels.
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Parallel algorithm a ( x, y ): an estimate of local space average color for each image pixel N ( x, y ): a set of neighboring elements ( 1 ) Average the data ( 2 ) Slowly add the color of the current pixel ( p : small percentage )
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Parallel algorithm The two equations, ( 1 )&( 2 ),are carried out until convergence. 1000, 2000, 3000, 4000, 5000
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Local space average color 1 50 200 1000 The parallel algorithm 1000
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Reference Ebner, M., 2001. Evolving color constancy for an artificial retina. Genetic Programming: Proc. of the 4thEuropean Conference, EuroGP 2001, Lake Como, Italy. Springer-Verlag, Berlin, pp. 11–22. Ebner, M., 2004. A parallel algorithm for color constancy. J. Parallel Distributed Comput. 64 (1), 79–88.
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Why Mondrian has been chosen First introduced by Edwin Land No curve and angle. No shade and texture. Neither uniformly colored nor uniformly bright. Resemble better the more colorful work of Klee or Lohse. Anya Hurlbert, 1999
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Paul Klee 南方突尼西亞人花園 Tunisian Gardens 1919 Ref. www.writedesignonline.com/history- culture/bauhaus.htm
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Richard Paul Lohse Thematic series in 18 colours A, 1982 Squares formed by colour groups 1944/2 Ref. www.lohse.ch/bio_e.html
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Mondrian Piet Mondrian, Composition A, 1923 www.cartage.org.lb/en/themes/Arts/p ainting/20th-century/art- sake/artsake.htm
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Typical Mondrian stimuli Yellowish daylight ; bluish daylight 2 grey papers ( third from the top on the left )
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The experiment of Kraft and Brainard Look through a window into a box A grey test surface against the back wall A Mondrian-like panel A tube wrapped in tin foil A cube, pyramid and tube made from grey cardboard
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Local surround Neutral-illuminant ; Orange-red
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Spatial Mean Neutral-illuminant ; pale-red
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Maximum Flux Neutral-illuminant ; yellow-illuminant
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Results Color constancy
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Anya Hurlbert, 2007 Unknown why humans need color constancy. Color? Shape? How is color constancy measured? with difficulty. Mondrians? How is color constancy achieved? More than one mechanism. Color processing in the brain. Retinex
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Reference Hurlbert A (1999) Colour vision: is colour constancy real? Current Biology 9:R558 – R561. Hurlbert, A. (2007). Colour constancy. Current Biology, 17(21), R906-7. JM Kraft and DH Brainard, Mechanisms of color constancy under nearly natural viewing. Proc Natl Acad Sci USA 96 (1999), pp. 307 – 312.
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