Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A relevance feedback mechanism for content-based image retrieval
Information Processing and Management: an International Journal
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Modern Information Retrieval
Order-based fitness functions for genetic algorithms applied to relevance feedback
Journal of the American Society for Information Science and Technology
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Signal Processing - Special section on content-based image and video retrieval
Modified hierarchical genetic algorithm for relevance feedback in image retrieval
Intelligent Data Analysis
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The emergence of multimedia technology and the rapid expansion of image sets on the internet have attracted a lot of research tools for effective retrieval of visual data. When working in the image retrieval context the main goal is to retrieve images which might be useful or relevant to the user based on features automatically extracted from the images. The proposal of this work is to integrate the information provided by the user into the decision procedure by the use of the relevance feedback mechanism. The relevance feedback technique used is based on genetic algorithms using a proposed order-based fitness function in order to adapt the user's image similarity criteria. Image similarity is expressed as a weighted integration of color, shape and texture features. The retrieval process itself is based on the Local Similarity Pattern, where the image areas are uniformly partitioned into regions, and the similarity between the images is measured by corresponding region similarities. The use of negative and positive weights for the features, into the genetic algorithm, allows one to express, in a continuous way, the concepts of relevance, irrelevance and undesirability in the similarity model used. Experiments in a database with 12750 images has shown that the integration of features through the proposed genetic algorithm into a relevance feedback mechanism provides good results in the image retrieval context.