IMAGE SEGMENTATION USING CURVE EVOLUTION AND
REGION STABILITY
Baris Sumengen, B.
S. Manjunath, and Charles Kenney
Dept. of Electrical and Computer
Engineering
University of California at Santa Barbara
Santa Barbara, CA 93106
Email: {sumengen, manj, kenney} @ece.ucsb.edu
Abstract
A novel scheme for
image segmentation is presented.
An image segmentation criterion is proposed that gathers
similar pixels together to form regions and creates
boundaries between two dissimilar regions. This criterion
is formulated as a cost function. This cost function is
minimized by using gradient-descent methods, which
leads to a curve evolution equation that segments the
image. The proposed method generalizes previous
methods to more complex similarity and distance
measures and can be applied to vector valued images
such as texture and color images.
