Design and evaluation of a content-based image retrieval system
Design and management of multimedia information systems
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Content-based image retrieval by combining genetic algorithm and support vector machine
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
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There have been two problems in the implementation of a contentbased image retrieval (CBIR) system in web. One is the absence of a standardized way to describe image content, the other is the disregard for the special needs of individual users To address these two problems, in this paper, a human-oriented CBIR system is presented which is implemented by applying MPEG-7 descriptors. In the new system, a multi-feature space is established and both homogeneous texture descriptor and color layout descriptor are used. Since there are difference in human perceptions of color and texture, in order to successfully retrieve an image which caters to the users, PGA (parallel genetic algorithm) is employed to adjust the weight of each feature space. The experimental evidence shows that the system is robust in general format by using MPEG-7 and it is capable of matching the user profile as well.