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A novel content based image retrieval system using K-means/KNN with feature extraction
Author(s) -
Ray-I Chang,
ShuYu Lin,
Jan-Ming Ho,
Chi-Wen Fann,
Yuchun Wang
Publication year - 2012
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis120122047c
Subject(s) - computer science , content based image retrieval , image retrieval , cluster analysis , feature extraction , pattern recognition (psychology) , k nearest neighbors algorithm , artificial intelligence , feature (linguistics) , image (mathematics) , segmentation , data mining , information retrieval , linguistics , philosophy
Image retrieval has been popular for several years. There are different system designs for content based image retrieval (CBIR) system. This paper propose a novel system architecture for CBIR system which combines techniques include content-based image and color analysis, as well as data mining techniques. To our best knowledge, this is the first time to propose segmentation and grid module, feature extraction module, K-means clustering and bring in the neighborhood module to build the CBIR system. Concept of neighborhood color analysis module which also recognizes the side of every grids of image is first contributed in this paper. The results show the CBIR systems performs well in the training and it also indicates there contains many interested issue to be optimized in the query stage of image retrieval.

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