Open AccessApplication of fuzzy set theory to color image retrieval*
Author(s) -
Yanmei Liang,
Hongchen Zhai,
Guoguang Mu
Publication year - 2002
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.51.2671
Subject(s) - rgb color model , artificial intelligence , color space , computer science , color histogram , color image , color balance , pattern recognition (psychology) , similarity (geometry) , fuzzy set , similarity measure , image retrieval , fuzzy logic , computer vision , relation (database) , color quantization , rgb color space , image (mathematics) , mathematics , data mining , image processing
We report an application of fuzzy relations in fuzzy set theory to the calculation of the similarity between colors, and apply it to the color image retrieval, where only a membership function is used as a measure of the similarity between the characteristic color vectors of a query image and of the images in the database. A match between two colors is defined as the α-cut fuzzy relation.In the comparison process, screening with decreasing by orders for comparisons and a method of regional color vector comparison are developed, which effectively reduce the color correlation in the red-green-blue (RGB) space and save from massive unnecessary calculations. Our theoretical and experimental results show clearly the advantages of our approach in both accuracy and speed of the color image retrieval.