Image Segmentation with Mrf Coupled Infinite Mixture Model
نویسنده
چکیده
Image segmentation is an important problem which addresses the needs of lots of biomedical applications. In this work, we adress the problem with MRF-coupled mixture models. In the standard finite mixture models, the number of segments that we are supposed to find in an image is fixed. With the Bayesian non-parametrics formulation we automatically find the number of segments by considering an infinite mixture model which consists of infinite number of clusters. We apply the MRF-coupled infinite mixture model on some biomedical images and show that with IMM, we are able to automatically determine the number of kinds of objects differing from the background.
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