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

1999

@inproceedings{MBS1999,
	vgclass =	{refpap},
	author =	{Jitendra Malik and Serge Belongie and Jianbo Shi and
	Thomas Leung},
	title =	{Textons, Contours and Regions: Cue Integration in Image
	Segmentation},
	booktitle =	{Proceedings of the Seventh IEEE International Conference on Computer Vision (ICCV'99)},
	address =	{Kerkyra, Greece},
	month =	{September},
	year =	{1999},
	url =	{http://www.cs.berkeley.edu/\~{}leungt/Research/ICCV99b_final.ps.gz},
	abstract =	{This paper makes two contributions. It provides (1) an
	operational definition of textons, the putative elementary units of
	texture perception, and (2) an algorithm for partitioning the image
	into disjoint regions of coherent brightness and texture, where
	boundaries of regions are defined by peaks in contour orientation
	energy and differences in texton densities across the contour. 

	Julesz introduced the term texton, analogous to a phoneme in speech
	recognition, but did not provide an operational definition for
	gray-level images. Here we re-invent textons as frequently co-occurring
	combinations of oriented linear filter outputs. These can be learned
	using a K-means approach. By mapping each pixel to its nearest texton,
	the image can be analyzed into texton channels, each of which is a
	point set where discrete techniques such as Voronoi diagrams become
	applicable. 

	Local histograms of texton frequencies can be used with a $\chi^2$ test
	for significant differences to find texture boundaries. Natural images
	contain both textured and untextured regions, so we combine this cue
	with that of the presence of peaks of contour energy derived from
	outputs of odd- and even-symmetric oriented Gaussian derivative
	filters. Each of these cues has a domain of applicability, so to
	facilitate cue combination we introduce a gating operator based on a
	statistical test for isotropy of Delaunay neighbors. Having obtained a
	local measure of how likely two nearby pixels are to belong to the same
	region, we use the spectral graph theoretic framework of normalized
	cuts to find partitions of the image into regions of coherent texture
	and brightness. Experimental results on a wide range of images are
	shown.},
}