IMAGE SEGMENTATION USING CURVE EVOLUTION AND FLOW
FIELDS
 
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

An image segmentation scheme that utilizes image-based
flow fields in a curve evolution framework is presented.
Geometric curve evolution methods require an edge
function and a vector field with certain characteristics
that are obtained from the image itself. A vector field
borrowed from the edgeflow segmentation method is
utilized both to obtain an edge function and to guide the
curve evolution towards the object boundaries. This
vector field is computed from the image using intensity,
texture and color features. The proposed method
integrates well-tested image features to the well-studied
curve evolution methods thus achieving better
segmentation results.