Active contour model driven by Self Organizing Maps for image segmentation

作者：

Highlights：

• A new function for computing local self-organizing clustering center with SOM clustering algorithm.

• An adaptive sign function is presented to replace the constant of the area term in the level set method that enables model to change motion direction of the level set.

• An improved double-well potential function is proposed to improve the stability of curve evolution.

• The proposed model shows better segmentation accuracy and robustness.

摘要

•A new function for computing local self-organizing clustering center with SOM clustering algorithm.•An adaptive sign function is presented to replace the constant of the area term in the level set method that enables model to change motion direction of the level set.•An improved double-well potential function is proposed to improve the stability of curve evolution.•The proposed model shows better segmentation accuracy and robustness.

论文关键词：Active contour model,Self Organizing Maps,Intensity inhomogeneity,Image segmentation

论文评审过程：Received 30 April 2020, Revised 21 January 2021, Accepted 24 March 2021, Available online 30 March 2021, Version of Record 6 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114948