Abstract
Snakes, or active contours, are one of the major paradigms in image segmentation. With the gradient vector flow (GVF) as external force, they have a larger capture range and the ability to progress into concave boundaries. However, when we have to deal with highly non-convex shapes, the GVF field forms an area where the forces point in opposite directions and the snake stops. GVF is built as a diffusion process of the gradient vectors of an edge map derived from the image. In this paper, we will view the diffusion process as a mechanism having the gradient vectors of the edge map as the input and the resulting GVF as the output. We will show how a modified input will result in a GVF able to drive the snake in such a highly non-convex boundary. This ability is revealed as a generalized property of the GVF diffusion process.
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