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.
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Lai, CC., Chen, YC. (2009). Color Image Retrieval Based on Interactive Genetic Algorithm. In: Chien, BC., Hong, TP., Chen, SM., Ali, M. (eds) Next-Generation Applied Intelligence. IEA/AIE 2009. Lecture Notes in Computer Science(), vol 5579. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02568-6_35
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DOI: https://doi.org/10.1007/978-3-642-02568-6_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02567-9
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