Robust Active Contour Model Using Patch-Based Signed Pressure Force and Optimized Fractional-Order Edge

Active contour models (ACMs) are the most widely used method for image segmentation. However, global fitting ACMs cannot effectively segment inhomogeneous images and local suffer from noise initial position of contour. To overcome these shortcomings, we propose a novel ACM that consists mainly term, an edge-based term external force term. The Jensen-Shannon divergence (JSD) based is implemented to address intensity inhomogeneity. formulated on Caputo-Fabrizio (CF) fractional-order Gaussian derivatives applied compute weighted area region inside patch-based designed improve robustness developed further proposed model noise, input first replaced with its robust statistics. Experimental results demonstrate not only but also effective in dealing