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Machine Vision and Applications

, Volume 21, Issue 5, pp 789–796 | Cite as

Is local colour normalization good enough for local appearance-based classification?

  • Donovan H. ParksEmail author
  • Martin D. Levine
Short Paper
  • 117 Downloads

Abstract

This paper evaluates the effectiveness of colour normalization techniques when they are applied to small image patches as opposed to the entire image. We evaluate five colour normalization techniques using three different local appearance-based classifiers. Our test sets allow us to independently examine the influence of illumination changes due to lighting colour and geometry. We demonstrate that local colour normalization can significantly improve the performance of a local appearance-based classifier. However, we observe that the effectiveness of local colour normalization depends on both the underlying classifier and the type of illumination variation.

Keywords

Colour normalization Colour constancy Object recognition Local appearance-based classifier Coherency filtering 

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Faculty of Computer ScienceDalhousie UniversityHalifaxCanada
  2. 2.Centre for Machine IntelligenceMcGill UniversityMontrealCanada

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