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Texture classification via conditional histograms

Aguado, A. S., Montiel, M. E. and Nixon, Mark (2005) Texture classification via conditional histograms Pattern Recognition Letters, 26, (11), pp. 1740-1751.

Record type: Article

Abstract

This paper presents a non-parametric discrimination strategy based on texture features characterised by one-dimensional conditional histograms. Our characterisation extends previous co-occurrence matrix encoding schemes by considering a mixture of colour and contextual information obtained from binary images. We compute joint distributions that define regions that represent pixels with similar intensity or colour properties. The main motivation is to obtain a compact characterisation suitable for applications requiring on-line training. Experimental results show that our approach can provide accurate discrimination. We use the classification to implement a segmentation application based on a hierarchical subdivision. The segmentation handles mixture problems at the boundary of regions by considering windows of different sizes. Examples show that the segmentation can accurately delineate image regions.

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Published date: 2005
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 268406
URI: http://eprints.soton.ac.uk/id/eprint/268406
PURE UUID: 0278d173-b553-4bf0-b1b4-2bee43fac11a

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Date deposited: 22 Jan 2010 15:31
Last modified: 18 Jul 2017 06:54

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Contributors

Author: A. S. Aguado
Author: M. E. Montiel
Author: Mark Nixon

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