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.
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.
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||22 Jan 2010 15:31|
|Last Modified:||02 Mar 2012 12:00|
|Contributors:||Aguado, A. S. (Author)
Montiel, M. E. (Author)
Nixon, Mark (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||9|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)