EVALUATION OF LOCAL ORIENTATION FOR TEXTURE CLASSIFICATION

Dana Elena Ilea, Ovidiu Ghita, Paul F. Whelan

2008

Abstract

The aim of this paper is to present a study where we evaluate the optimal inclusion of the texture orientation in the classification process. In this paper the orientation for each pixel in the image is extracted using the partial derivatives of the Gaussian function and the main focus of our work is centred on the evaluation of the local dominant orientation (which is calculated by combining the magnitude and local orientation) on the classification results. While the dominant orientation of the texture depends strongly on the observation scale, in this paper we propose to evaluate the macro-texture by calculating the distribution of the dominant orientations for all pixels in the image that sample the texture at micro-level. The experimental results were conducted on standard texture databases and the results indicate that the dominant orientation calculated at micro-level is an appropriate measure for texture description.

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Paper Citation


in Harvard Style

Ilea D., Ghita O. and Whelan P. (2008). EVALUATION OF LOCAL ORIENTATION FOR TEXTURE CLASSIFICATION . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 357-364. DOI: 10.5220/0001084603570364

in Bibtex Style

@conference{visapp08,
author={Dana Elena Ilea and Ovidiu Ghita and Paul F. Whelan},
title={EVALUATION OF LOCAL ORIENTATION FOR TEXTURE CLASSIFICATION},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={357-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001084603570364},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - EVALUATION OF LOCAL ORIENTATION FOR TEXTURE CLASSIFICATION
SN - 978-989-8111-21-0
AU - Ilea D.
AU - Ghita O.
AU - Whelan P.
PY - 2008
SP - 357
EP - 364
DO - 10.5220/0001084603570364