Hybrid Active Contour Driven by Double-Weighted Signed Pressure Force for Image Segmentation

In this paper, we proposed a novel hybrid active contour driven by double-weighted signed pressure force method for image segmentation. First, the Legendre polynomials and global information are integrated into the signed pressure force (SPF) function and a coefficient is applied to weight the effect degrees of the Legendre term and global term. Second, by introducing a weighted factor as the coefficient of inside and outside region fitting center, the curve can be optimally evolved to the interior and branches of the region of interest (ROI). Third, a new edge stopping function is adopted to robustly capture the edge of ROI and speed up the multi-object image segmentation. Experiments show that the proposed method can achieve better accuracy for images with noise, inhomogeneous intensity, blur edge and complex branches, in the meanwhile, it also controls the time-consuming effectively and is insensitive to the initial contour position.