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.

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