IMAGE SEGMENTATION USING CURVE EVOLUTION
 

Baris Sumengen, B. S. Manjunath, and Charles Kenney
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106-9560
{sumengen, manj, kenney}@ece.ucsb.edu
 

Abstract

A novel scheme for image segmentation is presented. The
technique is based on the integration of ideas from
geodesic active contours and a recently proposed
edgeflow segmentation. Given an image a 2-D vector is
constructed at each pixel location. This vector points in
the direction of potential boundary pixels. The
computation of the 2-D vector field is based on image
intensity, color and texture gradients. Following this, an
initial curve is instantiated and propagated to separate
the image into foreground and background regions. The
curve propagation is guided by the above mentioned
vector field. The proposed approach thus utilizes an edge-based
segmentation method and extends traditional PDE
based curve evolution methods to texture image
segmentation, and avoids the post-processing problems in
edge linking and boundary detection.