In this paper we use a variational Bayesian framework for color image segmentation. Each image is represented in the L*u*v color coordinate system before being segmented by the va...
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
A novel illumination invariant unsupervised multispectral texture segmentation method with unknown number of classes is presented. Multispectral texture mosaics are locally repres...
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...