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Authors: Rostom Kachouri 1 ; Khalifa Djemal 2 ; Hichem Maaref 2 ; Dorra Sellami Masmoudi 3 and Nabil Derbel 3

Affiliations: 1 Research unit on Computers, Imaging, Electronics and Systems, ENIS; Informatics, Integrative Biology and Complex Systems, France ; 2 Informatics, Integrative Biology and Complex Systems, France ; 3 Research unit on Computers, Imaging, Electronics and Systems, ENIS, Tunisia

Keyword(s): CBIR, SVM, QUIP-tree, feature extraction, heterogeneous image database.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Image Processing ; Informatics in Control, Automation and Robotics ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: Image databases represent increasingly important volume of information, so it is judicious to develop powerful systems to handle the images, index them, classify them to reach them quickly in these large image databases. In this paper, we propose an heterogeneous image retrieval system based on feature extraction and Support vector machines (SVM) classifier. For an heterogeneous image database, first of all we extract several feature kinds such as color descriptor, shape descriptor, and texture descriptor. Afterwards we improve the description of these features, by some original methods. Finally we apply an SVM classifier to classify the consequent index database. For evaluation purposes, using precision/recall curves on an heterogeneous image database, we looked for a comparison of the proposed image retrieval system with an other Content-based image retrieval (CBIR) which is QUadtree-based Index for image retrieval and Pattern search (QUIP-tree). The obtained results show that th e proposed system provides good accuracy recognition, and it prove more better than QUIP-tree method. (More)

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Paper citation in several formats:
Kachouri, R.; Djemal, K.; Maaref, H.; Sellami Masmoudi, D. and Derbel, N. (2008). HETEROGENEOUS IMAGE RETRIEVAL SYSTEM BASED ON FEATURES EXTRACTION AND SVM CLASSIFIER. In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO; ISBN 978-989-8111-32-6; ISSN 2184-2809, SciTePress, pages 137-142. DOI: 10.5220/0001490601370142

@conference{icinco08,
author={Rostom Kachouri. and Khalifa Djemal. and Hichem Maaref. and Dorra {Sellami Masmoudi}. and Nabil Derbel.},
title={HETEROGENEOUS IMAGE RETRIEVAL SYSTEM BASED ON FEATURES EXTRACTION AND SVM CLASSIFIER},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO},
year={2008},
pages={137-142},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001490601370142},
isbn={978-989-8111-32-6},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO
TI - HETEROGENEOUS IMAGE RETRIEVAL SYSTEM BASED ON FEATURES EXTRACTION AND SVM CLASSIFIER
SN - 978-989-8111-32-6
IS - 2184-2809
AU - Kachouri, R.
AU - Djemal, K.
AU - Maaref, H.
AU - Sellami Masmoudi, D.
AU - Derbel, N.
PY - 2008
SP - 137
EP - 142
DO - 10.5220/0001490601370142
PB - SciTePress