Color Image Retrieval Based on Interactive Genetic Algorithm

Authors:
Chih-Chin Lai;Ying-Chuan Chen
Affiliations:
Department of Electrical Engineering, National University of Kaohsiung, Kaohsiung, Taiwan 81148;Department of Computer Science and Information Engineering, National University of Tainan, Tainan, Taiwan 70005
Venue:
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Year:
2009

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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.