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Color feature extraction of regions by means of GA for scenery image retrieval
Author(s) -
Mitsukura Yasue,
Sakamoto Koji,
Fukai Hironobu,
Yoshimori Seiki,
Ito Seiji,
Fukumi Minoru
Publication year - 2012
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10364
Subject(s) - computer science , artificial intelligence , segmentation , image retrieval , pattern recognition (psychology) , image (mathematics) , relation (database) , feature (linguistics) , keyword extraction , feature extraction , image segmentation , genetic algorithm , computer vision , data mining , machine learning , linguistics , philosophy
Keyword image retrieval is now widely studied. By using such technologies, we can obtain images with the corresponding keywords easily. In the case of conventional image search systems, we basically search according to file names. However, the file names given are frequently incorrect. To resolve this problem, we propose an automatic keyword addition method for scenery images. In this paper, there are two important points. One is the image segmentation method using the maximum distance algorithm (MDA). The other is automatic keyword addition using the color features of regions. In the image segmentation method, we propose an automatic decision method for the parameters of the MDA. For this purpose, we investigate the relation between the optimal parameters and the features of regions. For the color feature extraction of regions, we propose a genetic algorithm (GA). Moreover, in order to show the effectiveness of the proposed method, we provide simulation examples. The results of simulations demonstrate the effectiveness of keyword addition for scenery images. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 95(2): 39–49, 2012; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/ecj.10364