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Authors: Chathurika Dharmagunawardhana 1 ; Sasan Mahmoodi 1 ; Michael Bennett 2 and Mahesan Niranjan 1

Affiliations: 1 University of Southampton, United Kingdom ; 2 University Hospital Southampton NHS Foundation Trust, United Kingdom

Keyword(s): Spatially Varying Parameters, Gaussian Markov Random Fields, Bayesian Modeling, Texture Classification, Texture Segmentation.

Related Ontology Subjects/Areas/Topics: Applications ; Bayesian Models ; Computer Vision, Visualization and Computer Graphics ; Feature Selection and Extraction ; Geometry and Modeling ; Image Understanding ; Image-Based Modeling ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: In statistical model based texture feature extraction, features based on spatially varying parameters achieve higher discriminative performances compared to spatially constant parameters. In this paper we formulate a novel Bayesian framework which achieves texture characterization by spatially varying parameters based on Gaussian Markov random fields. The parameter estimation is carried out by Metropolis-Hastings algorithm. The distributions of estimated spatially varying parameters are then used as successful discriminant texture features in classification and segmentation. Results show that novel features outperform traditional Gaussian Markov random field texture features which use spatially constant parameters. These features capture both pixel spatial dependencies and structural properties of a texture giving improved texture features for effective texture classification and segmentation.

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Paper citation in several formats:
Dharmagunawardhana, C.; Mahmoodi, S.; Bennett, M. and Niranjan, M. (2014). An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-018-5; ISSN 2184-4313, SciTePress, pages 139-146. DOI: 10.5220/0004752501390146

@conference{icpram14,
author={Chathurika Dharmagunawardhana. and Sasan Mahmoodi. and Michael Bennett. and Mahesan Niranjan.},
title={An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2014},
pages={139-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004752501390146},
isbn={978-989-758-018-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation
SN - 978-989-758-018-5
IS - 2184-4313
AU - Dharmagunawardhana, C.
AU - Mahmoodi, S.
AU - Bennett, M.
AU - Niranjan, M.
PY - 2014
SP - 139
EP - 146
DO - 10.5220/0004752501390146
PB - SciTePress

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