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Unsupervised texture segmentation based on the modified Markov random field model

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2 Author(s)
Yu Xiaohan ; Graphic Arts Lab., Tech. Res. Centre of Finland, Espoo, Finland ; Juha Yla-Jaaski

The Gaussian-Markov random field (MRF) model is a very useful technique for image processing, such as feature extraction and data compression. However its strict stability condition makes the model identification complex. The major problem is the choice of a proper support region for the model. In this paper a new model is proposed which is based on the MRF model and called the modified Gaussian-Markov random field model. It is not an optimal MRF model but has a very useful property, namely decorrelation. A stable modified MRF model always exists even if a stable MRF model does not exist on the given support region. Applications to texture segmentation are also presented

Published in:

Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on

Date of Conference:

30 Aug-3 Sep 1992

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