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), 1740-1751.

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Description/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.

Item Type: Article
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 268406
Date Deposited: 22 Jan 2010 15:31
Last Modified: 27 Mar 2014 20:15
Further Information:Google Scholar
ISI Citation Count:9
URI: http://eprints.soton.ac.uk/id/eprint/268406

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