Refereed full papers (journals, book chapters, international conferences)

1996

@inproceedings{HPB1996,
	vgclass =	{refpap},
	author =	{Thomas Hofmann and Jan Puzicha and Joachim Buhmann},
	title =	{Unsupervised Segmentation of Textured Images by Pairwise
	Data Clustering},
	editor =	{P. Delogne},
	booktitle =	{IEEE International Conference on Image Processing (ICIP'96)},
	address =	{Lausanne, Switzerland},
	pages =	{137--140},
	month =	{September},
	year =	{1996},
	url =	{http://www-dbv.informatik.uni-bonn.de/postscript/hofmann.icip96.ps.gz},
	abstract =	{We propose a novel approach to unsupervised texture
	segmentation, which is formulated as a combinatorial optimization
	problem known as pairwise data clustering with a sparse neighborhood
	structure. Pairwise dissimilarities between texture blocks are measured
	in terms of distribution differences of multi-resolution features. The
	feature vectors are based an a Gabor wavelet image representation. 

	To efficiently solve the data clustering problem a deterministic
	annealing algorithm based on a meanfield approximation is derived. An
	application to Brodatz-like microtexture mixtures is shown. We
	statistically adress the questions of adequacy of the proposed cost
	function and the quality of the deterministic annealing algorithm
	compared with its stochastic variants.},
}