Image Segmentation Based on Active Contour Derived by Signed Pressure Force Function

Authors

Hongli Lü, 1. College of Mathematics and information Science, Wenzhou University, Zhejiang 325035, China;;
Renfang Wang, 2. College of Computer Science and Information Technology, Zhejiang Wanli University, Ningbo 315100, China;

Abstract

Abstract: Distance regularized level set evolution model for image segmentation has some shortcomings. Initial curve is not flexible and the direction of curve evolution is not self-adaptive. A new active contour model was proposed. A signed pressure force function (SPF) was constructed, integrating local information and global information, and shown to modulate the signs of pressure forces inside and outside the region of object; Then SPF was embed to DRLSE model to solve the problem of requiring the initial contour to surround (let in or keep out) the objects. Experimental results show that the new model's initial contour can be placed anywhere in the image, the new model can effectively segment images with intensity inhomogeneity and weak boundaries and it can effectively segment images containing multi-objects or deep recessed area.

Recommended Citation

Lü, Hongli and Wang, Renfang (2020) "Image Segmentation Based on Active Contour Derived by Signed Pressure Force Function," Journal of System Simulation: Vol. 28: Iss. 1, Article 24.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss1/24

First Page

174

Revised Date

2014-09-15

DOI Link

https://doi.org/

Last Page

182

CLC

TP.391.41

Recommended Citation

Lü Hongli, Wang Renfang. Image Segmentation Based on Active Contour Derived by Signed Pressure Force Function[J]. Journal of System Simulation, 2016, 28(1): 174-182.