Robust level set image segmentation via a local correntropy-based K-means clustering

作者：

Highlights：

• We propose a level set segmentation method based on the local correntropy-based K-means (LCK) clustering.

• Due to LCK clustering, our segmentation algorithm is robust to complex noise.

• Segmentation accuracy is improved as compared with the state-of-the-art approaches.

摘要

Highlights•We propose a level set segmentation method based on the local correntropy-based K-means (LCK) clustering.•Due to LCK clustering, our segmentation algorithm is robust to complex noise.•Segmentation accuracy is improved as compared with the state-of-the-art approaches.

论文关键词：Image segmentation,Level set,Correntropy-based K-means

论文评审过程：Received 7 August 2013, Revised 5 November 2013, Accepted 13 November 2013, Available online 21 November 2013.

论文官网地址：https://doi.org/10.1016/j.patcog.2013.11.014