A taxonomy of color constancy and invariance algorithm

Abstract

Color is an effective cue for identifying regions of interest or objects for a wide range of applications in computer vision and digital image processing research. However, color information in recorded image data, typically represented in RGB format, is not always an intrinsic property of an object itself, but rather it also depends on the illumination condition and sensor characteristic. When these factors are not properly taken into consideration, the performance of color analysis system can deteriorate significantly. This chapter investigates two common methodologies to attain reliable color description of recorded image data, color constancy and color invariance. Comprehensive overview of existing techniques are presented. Further, fundamental physical models of light reflection, and a color image formation process in typical imaging devices are discussed, which provide important underlying concepts for various color constancy and invariance algorithms. Finally, two experiments are demonstrated to evaluate the performance of representative color constancy and invariance algorithms.