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Authors: Ismail Elsayad ; Jean Martinet ; Thierry Urruty ; Taner Danisman ; Haidar Sharif and Chabane Djeraba

Affiliation: Lille 1 University, France

Keyword(s): SURF, Bag-of-visual-words, Visual phrases, Gaussian mixture model, Spatial weighting.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computer Vision, Visualization and Computer Graphics ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Image Formation and Preprocessing ; Implementation of Image and Video Processing Systems ; Informatics in Control, Automation and Robotics ; Sensor Networks ; Signal Processing ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing ; Statistical Approach ; Structural and Syntactic Approach

Abstract: Nowadays, having effective methods for accessing the desired images is essential with the huge amount of digital images. The aim of this paper is to build a meaningful mid-level representation of visual documents to be used later for matching between the query image and other images in the desired database. The approach is based firstly on constructing different visual words using local patch extraction and fusion of descriptors. Then, we represent the spatial constitution of an image as a mixture of n Gaussians in the feature space. Finally, we extract different association rules between frequent visual words in the local context of the image to construct visual phrases. Experimental results show that our approach outperforms the results of traditional image retrieval techniques.

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Paper citation in several formats:
Elsayad, I.; Martinet, J.; Urruty, T.; Danisman, T.; Sharif, H. and Djeraba, C. (2010). USING ASSOCIATION RULES AND SPATIAL WEIGHTING FOR AN EFFECTIVE CONTENT BASED-IMAGE RETRIEVAL. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP; ISBN 978-989-674-028-3; ISSN 2184-4321, SciTePress, pages 112-117. DOI: 10.5220/0002836101120117

@conference{visapp10,
author={Ismail Elsayad. and Jean Martinet. and Thierry Urruty. and Taner Danisman. and Haidar Sharif. and Chabane Djeraba.},
title={USING ASSOCIATION RULES AND SPATIAL WEIGHTING FOR AN EFFECTIVE CONTENT BASED-IMAGE RETRIEVAL},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP},
year={2010},
pages={112-117},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002836101120117},
isbn={978-989-674-028-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP
TI - USING ASSOCIATION RULES AND SPATIAL WEIGHTING FOR AN EFFECTIVE CONTENT BASED-IMAGE RETRIEVAL
SN - 978-989-674-028-3
IS - 2184-4321
AU - Elsayad, I.
AU - Martinet, J.
AU - Urruty, T.
AU - Danisman, T.
AU - Sharif, H.
AU - Djeraba, C.
PY - 2010
SP - 112
EP - 117
DO - 10.5220/0002836101120117
PB - SciTePress