Active contours driven by global and local weighted signed pressure force for image segmentation

作者：

Highlights：

• The novel global weighted SPF (GWSPF) is defined by introducing the normalized global minimum absolute differences as the coefficients of global inner and outer region fitting centers.

• The novel local weighted SPF (LWSPF) is similarly defined by introducing the normalized local minimum absolute differences as the coefficients of local inner and outer region fitting centers.

• The global and local within-class variances of the image are used to weight the GWSPF and the LWSPF, which can automatically adjust the effect degrees of the GWSPF and the LWSPF.

• The proposed model is superior to state-of-the-art active contour models in segmentation accuracy, in addition, it is robust to the initial curve.

摘要

•The novel global weighted SPF (GWSPF) is defined by introducing the normalized global minimum absolute differences as the coefficients of global inner and outer region fitting centers.•The novel local weighted SPF (LWSPF) is similarly defined by introducing the normalized local minimum absolute differences as the coefficients of local inner and outer region fitting centers.•The global and local within-class variances of the image are used to weight the GWSPF and the LWSPF, which can automatically adjust the effect degrees of the GWSPF and the LWSPF.•The proposed model is superior to state-of-the-art active contour models in segmentation accuracy, in addition, it is robust to the initial curve.

论文关键词：Active contour,GWSPF,LWSPF,Global and local within-class variances

论文评审过程：Received 23 April 2018, Revised 15 December 2018, Accepted 19 December 2018, Available online 20 December 2018, Version of Record 24 December 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.12.028