A Novel Content Based Image Retrieval System using K-means/KNN with Feature Extraction

Ray-I Chang1, Shu-Yu Lin1, 2, Jan-Ming Ho2, Chi-Wen Fann2 and Yu-Chun Wang2

  1. Dept. of Engineering Science and Ocean Engineering, National Taiwan University
    Taipei, Taiwan (R.O.C)
    {rayichang, d96525009}@ntu.edu.tw
  2. Research Center for Information Technology Innovation, Academia Sinica
    Taipei, Taiwan (R.O.C)
    {boymike, hoho, fann, zxaustin}@iis.sinica.edu.tw


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 and k-nearest neighbor clustering algorithms 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.

Key words

content based images retrieval; K-means clustering; feature extraction; image retrieval

Digital Object Identifier (DOI)


Publication information

Volume 9, Issue 4 (December 2012)
Special Issue on Recent Advances in Systems and Informatics
Year of Publication: 2012
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Chang, R., Lin, S., Ho, J., Fann, C., Wang, Y.: A Novel Content Based Image Retrieval System using K-means/KNN with Feature Extraction. Computer Science and Information Systems, Vol. 9, No. 4, 1645-1662. (2012), https://doi.org/10.2298/CSIS120122047C