DocumentCode :
1680255
Title :
Application of ant colony algorithm in image features extraction and identification
Author :
Zhang, Ying ; Chen, Xuebo
Author_Institution :
Sch. of Electron. & Inf. Eng., Liaoning Univ. of Sci. & Technol., Anshan, China
fYear :
2010
Firstpage :
873
Lastpage :
877
Abstract :
This paper proposes algorithms of image features extaction and identification by using seeking optimization capability of ant colony algorithm. The feature vectors of the identified images are regarded as the inputs of ant colony algorithm based on the information entropy. By the algorithms proposed by this paper, the features which cost the least time and whose identification effect are the best are selected under the precondition of identifying images correctly and then the images are identified. Experiments show that the algorithms are effective.
Keywords :
entropy; feature extraction; optimisation; ant colony algorithm; image features extraction; image features identification; information entropy; optimization capability; Ant colony optimization; Automation; Computer science; Feature extraction; MATLAB; Operations research; Optimization; ant colony algorithm; clustering; image identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554169
Filename :
5554169
Link To Document :
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