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Color classification of natural color images
Author(s) -
Tominaga Shoji
Publication year - 1992
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.5080170405
Subject(s) - color histogram , color space , color balance , color quantization , artificial intelligence , color normalization , color image , icc profile , pattern recognition (psychology) , computer vision , high color , false color , computer science , color model , color difference , histogram equalization , color depth , histogram , mathematics , image processing , image (mathematics) , enhanced data rates for gsm evolution
The present article describes a color classification method that partitions a color image into a set of uniform color regions. The input image data are first mapped from device coordinates into the CIE L*a*b* color space, an approximately uniform perceptual color space. Colors used to represent a natural color image are classified by means of cluster detection in the uniform color space. The basic process of color classification is based on histogram analysis to detect color clusters sequentially. The principal components of a color distribution are extracted for effective discrimination of clusters. We present an algorithm for sequential detection of color clusters in the uniform color space, and the related algorithms for region processing and color computation. The performance of the method is discussed in an experiment using three kinds of natural color images.