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Color Image Retrieval Based on Interactive Genetic Algorithm

  • Chih-Chin Lai
  • Ying-Chuan Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5579)

Abstract

In order to efficiently and effectively retrieval the desired images from a large image database, the development of a user-friendly image retrieval system has been an important research for several decades. In this paper, we propose a content-based image retrieval method based on an interactive genetic algorithm (IGA). The mean value and the standard deviation of a color image are used as color features. In addition, we also considered the entropy based on the gray level co-occurrence matrix as the texture feature. Further, to bridge the gap between the retrieving results and the users’ expectation, the IGA is employed such that the users can adjust the weight for each image according to their expectations. Experimental results are provided to illustrate the feasibility of the proposed approach.

Keywords

Content-based image retrieval interactive genetic algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Chih-Chin Lai
    • 1
  • Ying-Chuan Chen
    • 2
  1. 1.Department of Electrical EngineeringNational University of KaohsiungKaohsiungTaiwan
  2. 2.Department of Computer Science and Information EngineeringNational University of TainanTainanTaiwan

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