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ICPR
2008
IEEE

Using covariance matrices for unsupervised texture segmentation

11 years 1 months ago
Using covariance matrices for unsupervised texture segmentation
In this paper we propose an efficient unsupervised texture segmentation method. We introduce the extension of a state-of-the-art segmentation algorithm, which is exclusively based on color cues, by incorporating texture information. We further show how to use covariance matrices of low level features for texture description which can be efficiently calculated based on integral images. Furthermore, a multi-scale extension allows to provide accurate texture segmentation results. An experimental evaluation on a synthetic texture database and images of the Berkeley image database demonstrate the improved performance of the algorithm.
Horst Bischof, Michael Donoser
Added 05 Nov 2009
Updated 06 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Horst Bischof, Michael Donoser
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