Image Segmentation Using Active Contours With Normally Biased GVF External Force

Abstract

Gradient vector flow (GVF) is an effective external force for active contours, but its isotropic nature handicaps its performance. The recently proposed NGVF model is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it is sensitive to noise and could erase weak boundaries. In this letter, the normally biased GVF (NBGVF) external force is proposed for snake models, which keeps the diffusion along the tangential direction of the isophotes and biases that along the normal direction. The biasing weight approaches zero at boundaries and is 1 in homogeneous regions. Consequently, the NBGVF snake can preserve weak edges and smooth out noise while maintaining other desirable properties of GVF and NGVF snakes such as enlarged capture range, insensitivity to initialization and convergence to u-shape concavity. These properties are evaluated on synthetic and real images.