UNSUPERVISED IMAGE SEGMENTATION BASED ON THE MULTI-RESOLUTION INTEGRATION OF ADAPTIVE LOCAL TEXTURE DESCRIPTORS

Dana E. Ilea, Paul F. Whelan, Ovidiu Ghita

2010

Abstract

The major aim of this paper consists of a comprehensive quantitative evaluation of adaptive texture descriptors when integrated into an unsupervised image segmentation framework. The techniques involved in this evaluation are: the standard and rotation invariant Local Binary Pattern (LBP) operators, multi-channel texture decomposition based on Gabor filters and a recently proposed technique that analyses the distribution of dominant image orientations at both micro and macro levels. The motivation to investigate these texture analysis approaches is twofold: (a) they evaluate the texture information at micro-level in small neighborhoods and (b) the distributions of the local features calculated from texture units describe the texture at macro-level. This adaptive scenario facilitates the integration of the texture descriptors into an unsupervised clustering based segmentation scheme that embeds a multi-resolution approach. The conducted experiments evaluate the performance of these techniques and also analyse the influence of important parameters (such as scale, frequency and orientation) upon the segmentation results.

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Paper Citation


in Harvard Style

Ilea D., Whelan P. and Ghita O. (2010). UNSUPERVISED IMAGE SEGMENTATION BASED ON THE MULTI-RESOLUTION INTEGRATION OF ADAPTIVE LOCAL TEXTURE DESCRIPTORS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 134-141. DOI: 10.5220/0002822301340141


in Bibtex Style

@conference{visapp10,
author={Dana E. Ilea and Paul F. Whelan and Ovidiu Ghita},
title={UNSUPERVISED IMAGE SEGMENTATION BASED ON THE MULTI-RESOLUTION INTEGRATION OF ADAPTIVE LOCAL TEXTURE DESCRIPTORS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={134-141},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002822301340141},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - UNSUPERVISED IMAGE SEGMENTATION BASED ON THE MULTI-RESOLUTION INTEGRATION OF ADAPTIVE LOCAL TEXTURE DESCRIPTORS
SN - 978-989-674-029-0
AU - Ilea D.
AU - Whelan P.
AU - Ghita O.
PY - 2010
SP - 134
EP - 141
DO - 10.5220/0002822301340141