Image segmentation using multi-region stability and edge strength
 
Baris Sumengen, B. S. Manjunath, and Charles Kenney
Dept. of Electrical and Computer Engineering
University of California at Santa Barbara,
Santa Barbara, CA 93106
E-mail: {sumengen, manj, kenney}@ece.ucsb.edu

Abstract

A novel scheme for image segmentation is presented.
An image segmentation criterion is proposed that groups
similar pixels together to form regions. This criterion is
formulated as a cost function. This cost function is
minimized by using gradient-descent methods, which lead
to a curve evolution equation that segments the image into
multiple homogenous regions. Homogeneity is specified
through a pixel-to-pixel similarity measure, which is
defined by the user and can be adaptive based on the
current application. To improve the performance of the
system, an edge function is also used to adjust the speed
of the competing curves. The proposed method can be
easily applied to vector valued images such as texture and
color images without a significant addition to
computational complexity.