FEATURE VECTOR APPROXIMATION BASED ON WAVELET NETWORK

Mouna Dammak, Mahmoud Mejdoub, Mourad Zaied, Chokri Ben Amar

2012

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.

Paper Citation

in Harvard Style

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 1: ICAART, ISBN 978-989-8425-95-9, pages 394-399. DOI: 10.5220/0003776803940399

in Bibtex Style

@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 1: ICAART,},
year={2012},
pages={394-399},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003776803940399},
isbn={978-989-8425-95-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - FEATURE VECTOR APPROXIMATION BASED ON WAVELET NETWORK
SN - 978-989-8425-95-9
AU - Dammak M.
AU - Mejdoub M.
AU - Zaied M.
AU - Ben Amar C.
PY - 2012
SP - 394
EP - 399
DO - 10.5220/0003776803940399