We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
We investigate a method to speed up the O(n3 ) labeling algorithm of Rosenfeld and Pfaltz for segmenting binary images, which is unduly complex for large images. That algorithm sea...
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Many natural textures comprise structural patterns and show strong self-similarity. We use affine symmetry to segment an image into self-similar regions; that is a patch of textu...
In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...