Set-permutation-occurrence matrix based texture segmentation

Zwiggelaar, R., Blot, L., Raba, D and Denton, E. R. E (2003) Set-permutation-occurrence matrix based texture segmentation. In: Pattern Recognition and Image Analysis. Lecture Notes in Computer Science, 2652 . Springer Berlin / Heidelberg, pp. 1099-1107.

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Abstract

We have investigated a combination of statistical modelling and expectation maximisation for a texture based approach to the segmentation of mammographic images. Texture modelling is based on the implicit incorporation of spatial information through the introduction of a set-permutation-occurrence matrix. Statistical modelling is used for data generalisation and noise removal purposes. Expectation maximisation modelling of the spatial information in combination with the statistical modelling is evaluated. The developed segmentation results are used for automatic mammographic risk assessment.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 07 Mar 2011 12:52
Last Modified: 25 Jul 2019 03:27
URI: https://ueaeprints.uea.ac.uk/id/eprint/23922
DOI: 10.1007/978-3-540-44871-6_127

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