DocumentCode :
3487712
Title :
A color palette reduction method using multiobjective evolutionary clustering algorithm
Author :
Sadohira, Motonari ; Saito, Akio ; Aguirre, Hernan ; Tanaka, Kiyoshi
Author_Institution :
Fac. of Eng., Shinshu Univ., Nagano, Japan
fYear :
2011
fDate :
23-26 Aug. 2011
Firstpage :
238
Lastpage :
243
Abstract :
When we display color images on low devices having a limited number of pixels and/or colors, the technique called “color palette reduction” which reduces the colors in color palette to represent the input image with a limited number of colors is often used. In the color reduction process, we should select representative colors by considering color distribution of the input image so that the error between the approximated image and the original one becomes minimum. In this work, we try to use a new clustering approach called MOCK [1], which uses multi-objective evolutionary algorithm as the mean of clustering, and verify the basic performance of the proposed approach through computer simulation using several benchmark color images.
Keywords :
approximation theory; evolutionary computation; image colour analysis; image representation; pattern clustering; MOCK clustering approach; color distribution; color images; color palette reduction method; image approximation; multiobjective evolutionary clustering algorithm; representative color; Benchmark testing; Clustering algorithms; Color; Data models; IP networks; Image color analysis; Mathematical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and Signal Processing (PacRim), 2011 IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
ISSN :
1555-5798
Print_ISBN :
978-1-4577-0252-5
Electronic_ISBN :
1555-5798
Type :
conf
DOI :
10.1109/PACRIM.2011.6032899
Filename :
6032899
Link To Document :
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