Adaptive image retrieval through the use of a genetic algorithm

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S. F. da Silva , M. A. Batista and C. A. Z. Barcelos: Adaptive image retrieval through the use of a genetic algorithm. Proc. 19th IEEE Int. Conf. Tools With Artif. Intell., pp. 557-564, 2007



In this work an image retrieval system adaptable to user's interests by the use of relevance feedback via genetic algorithm is presented. The retrieval process is based on local similarity patterns. The goal of the genetic algorithm is to infer weights for regions and features that better translate the user's requirements producing better quality rankings. The genetic algorithm used has as its main innovation an order-based fitness function, which is appropriate to the ranking requirements of a majority of the users. This fitness function will quickly drive the genetic algorithm in the process of searching for an optimal solution. Evaluations in several databases have shown the robustness and efficiency of the proposed retrieval method even when the query is a sketch or damaged image.

Extended Abstract


author={S. F. D. Silva and M. A. Batista and C. A. Z. Barcelos},
booktitle={19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)},
title={Adaptive Image Retrieval through the Use of a Genetic Algorithm},
keywords={genetic algorithms;image retrieval;relevance feedback;adaptive image retrieval;genetic algorithm;order-based fitness function;relevance feedback;similarity patterns;Artificial intelligence;Biological cells;Feedback;Genetic algorithms;Image databases;Image retrieval;Information retrieval;Robustness;Spatial databases;Technological innovation},
url={ },

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