Title :
Morphological color quantization
Author :
Gibson, Stuart ; Harvey, Richard
Author_Institution :
Sch. of Inf. Syst., East Anglia Univ., Norwich, UK
Abstract :
Color histograms are a central feature in many image retrieval systems. Indeed they are part of the MPEG-7 standard. But histograms suffer from the "curse of dimensionality " in which the number of bins increases exponentially with the number of dimensions. There is therefore an imperative for methods for simplifying histograms. This paper presents a new method for simplifying histograms based on a cascade of increasing-scale graph morphology filters. The system we choose preserves scale space causality and so preserves the modes of the histogram. The method is quick to compute so is therefore a practically useful feature. We present results using the MPEG-7 Common Color Dataset that show that these new compressed features have a retrieval performance that is equivalent to full histograms.
Keywords :
computer vision; image retrieval; quantisation (signal); MPEG-7 common color dataset; MPEG-7 standard; color histograms; image retrieval systems; increasing-scale graph morphology filters; morphological color quantization; retrieval performance; scale space causality; Application software; Computer vision; Histograms; Image coding; Image retrieval; Information retrieval; Information systems; MPEG 7 Standard; Morphology; Quantization;
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1272-0
DOI :
10.1109/CVPR.2001.991007