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Dynamic Learning of Indexing Concepts for Home Image Retrieval
Abstract : This paper presents a component of a content based image retrieval system dedicated to let a user define the indexing terms used later during retrieval. A user inputs a indexing term name, image examples and counter-examples of the term,and the system learns a model of the concept as well as a similarity measure for this term. The similarity measure is based on weights reflecting the importance of each low-level feature extracted from the images. The system computes these weights using a genetic algorithm. Rating a particular similarity measure is done by clustering the examples and counter-examples using these weights and computing the quality of the obtained clusters. Experiments are conducted and results are presented on a set of 600 images.
Keywords :
Image Indexing Genetic Algorithms retrieval
Cited literature [15 references]
https://hal.inria.fr/hal-00953933
Contributor : Marie-Christine Fauvet <>
Submitted on : Monday, March 3, 2014 - 12:49:24 PM
Last modification on : Tuesday, December 8, 2020 - 10:42:46 AM
Long-term archiving on: : Saturday, May 31, 2014 - 10:51:42 AM
Contributor : Marie-Christine Fauvet <>
Submitted on : Monday, March 3, 2014 - 12:49:24 PM
Last modification on : Tuesday, December 8, 2020 - 10:42:46 AM
Long-term archiving on: : Saturday, May 31, 2014 - 10:51:42 AM
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Bissol_CBMI03.pdf
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