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A Fully Unsupervised Texture Segmentation Algorithm

Fauzi, Mohammad F. A. and Lewis, Paul H., (2003) A Fully Unsupervised Texture Segmentation Algorithm Harvey, Richard and Bangham, J. Andrew (eds.) At British Machine Vision Conference 2003, United Kingdom. 09 - 11 Sep 2003. , pp. 519-528.

Record type: Conference or Workshop Item (Other)


This paper presents a fully unsupervised texture segmentation algorithm by using a modified discrete wavelet frames decomposition and a mean shift algorithm. By fully unsupervised, we mean the algorithm does not require any knowledge of the type of texture present nor the number of textures in the image to be segmented. The basic idea of the proposed method is to use the modified discrete wavelet frames to extract useful information from the image. Then, starting from the lowest level, the mean shift algorithm is used together with the fuzzy c-means clustering to divide the data into an appropriate number of clusters. The data clustering process is then refined at every level by taking into account the data at that particular level. The final crispy segmentation is obtained at the root level. This approach is applied to segment a variety of composite texture images into homogeneous texture areas and very good segmentation results are reported.

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Published date: 2003
Additional Information: Event Dates: 9 - 11 September 2003
Venue - Dates: British Machine Vision Conference 2003, United Kingdom, 2003-09-09 - 2003-09-11
Keywords: Texture segmentation, discrete wavelet frames, mean-shift clustering, fuzzy clustering
Organisations: Web & Internet Science


Local EPrints ID: 258261
PURE UUID: e2ddd25d-b6b2-4dc5-a6b0-13593f8e632d

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Date deposited: 18 Oct 2003
Last modified: 18 Jul 2017 09:34

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Author: Mohammad F. A. Fauzi
Author: Paul H. Lewis
Editor: Richard Harvey
Editor: J. Andrew Bangham

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