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Authors: Muhammad Rushdi and Jeffrey Ho

Affiliation: University of Florida, United States

ISBN: 978-989-8425-47-8

Keyword(s): Texture classification, Texton, Sparse representation, Image dictionary.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Early Vision and Image Representation ; Feature Extraction ; Features Extraction ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing ; Statistical Approach

Abstract: This paper addresses the problem of texture classification under unknown viewpoint and illumination variations. We propose an approach that combines sparse K-SVD and texton-based representations. Starting from an analytic or data-driven base dictionary, a sparse dictionary is iteratively estimated from the texture data using the doubly-sparse K-SVD algorithm. Then, for each texture image, K-SVD representations of pixel neighbourhoods are computed and used to assign the pixels to textons. Hence, the texture image is represented by the histogram of its texton map. Finally, a test image is classified by finding the closest texton histogram using the chi-squared distance. Initial experiments on the CUReT database show high classification rates that compare well with Varma-Zisserman MRF results.

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Paper citation in several formats:
Rushdi, M. and Ho, J. (2011). TEXTURE CLASSIFICATION USING SPARSE K-SVD TEXTON DICTIONARIES.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 187-193. DOI: 10.5220/0003376101870193

@conference{visapp11,
author={Muhammad Rushdi. and Jeffrey Ho.},
title={TEXTURE CLASSIFICATION USING SPARSE K-SVD TEXTON DICTIONARIES},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={187-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003376101870193},
isbn={978-989-8425-47-8},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - TEXTURE CLASSIFICATION USING SPARSE K-SVD TEXTON DICTIONARIES
SN - 978-989-8425-47-8
AU - Rushdi, M.
AU - Ho, J.
PY - 2011
SP - 187
EP - 193
DO - 10.5220/0003376101870193

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