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} [at] 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.

[PDF] [BibTex] See also: #206
B. Sumengen, B. S. Manjunath, C. Kenney,
IEEE International Conference on Image Processing (ICIP), Rochester, NY, USA, Sep. 2002.
Node ID: 349 , DB ID: 147 , VRLID: 107 , Lab: VRL , Target: Proceedings
Subject: [Detection on Images and Videos] « Look up more