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Authors: Mouna Dammak ; Mahmoud Mejdoub ; Mourad Zaied and Chokri Ben Amar

Affiliation: ENIS University, Tunisia

Keyword(s): Wavelet network, Approximation, Local feature, Bag of words.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods ; Vision and Perception

Abstract: Image classification is an important task in computer vision. In this paper, we propose a new image representation based on local feature vectors approximation by the wavelet networks. To extract an approximation of the feature vectors space, a Wavelet Network algorithm based on fast Wavelet is suggested. Then, the K-nearest neighbor (K-NN) classification algorithm is applied on the approximated feature vectors. The approximation of the feature space ameliorates the feature vector classification accuracy.

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Paper citation in several formats:
Dammak, M.; Mejdoub, M.; Zaied, M. and Ben Amar, C. (2012). FEATURE VECTOR APPROXIMATION BASED ON WAVELET NETWORK. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-95-9; ISSN 2184-433X, SciTePress, pages 394-399. DOI: 10.5220/0003776803940399

@conference{icaart12,
author={Mouna Dammak. and Mahmoud Mejdoub. and Mourad Zaied. and Chokri {Ben Amar}.},
title={FEATURE VECTOR APPROXIMATION BASED ON WAVELET NETWORK},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2012},
pages={394-399},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003776803940399},
isbn={978-989-8425-95-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - FEATURE VECTOR APPROXIMATION BASED ON WAVELET NETWORK
SN - 978-989-8425-95-9
IS - 2184-433X
AU - Dammak, M.
AU - Mejdoub, M.
AU - Zaied, M.
AU - Ben Amar, C.
PY - 2012
SP - 394
EP - 399
DO - 10.5220/0003776803940399
PB - SciTePress

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