Share Email Print

Proceedings Paper

A new improved local Chan-Vese model
Author(s): Ming Shen; Yiping Wu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Based on the local image information, we propose a new improved local active contour model to segment inhomogeneous images. The level set evolution equation of the proposed model which is different from improved Chan- Vese (ICV) model and local Chan-Vese (LCV) model is ordinary differential equation. Without mean curvature and other complicate difference items, the implementation becomes simpler by employing a finite difference scheme, thus the efficiency of global segmentation is dramatically improved. Experimental results on synthetic images as well as real medical images are shown in the paper to demonstrate the segmentation accuracy, efficiency and robustness of the proposed method.

Paper Details

Date Published: 4 March 2015
PDF: 5 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 944332 (4 March 2015); doi: 10.1117/12.2179939
Show Author Affiliations
Ming Shen, Fuzhou Univ. (China)
Yiping Wu, Fuzhou Univ. (China)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top