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Color angular indexing

  • Graham D. Finlayson
  • Subho S. Chatterjee
  • Brian V. Funt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)

Abstract

A fast color-based algorithm for recognizing colorful objects and colored textures is presented. Objects and textures are represented by just six numbers. Let r, g and b denote the 3 color bands of the image of an object (stretched out as vectors) then the color angular index comprises the 3 inter-band angles (one per pair of image vectors). The color edge angular index is calculated from the image's color edge map (the Laplacian of the color bands) in a similar way. These angles capture important low-order statistical information about the color and edge distributions and invariant to the spectral power distribution of the scene illuminant. The 6 illumination-invariant angles provide the basis for angular indexing into a database of objects or textures and has been tested on both Swain's database of color objects which were all taken under the same illuminant and Healey and Wang's database of color textures which were taken under several different illuminants. Color angular indexing yields excellent recognition rates for both data sets.

Keywords

Color Indexing Distribution Angle Color Histogram Color Distribution Color Constancy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Graham D. Finlayson
    • 1
  • Subho S. Chatterjee
    • 2
  • Brian V. Funt
    • 2
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK
  2. 2.School of Computing ScienceSimon Fraser UniversityVancouverCanada

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