Ziplock Snakes

作者:Walter M. Neuenschwander, Pascal Fua, Lee Iverson, Gábor Székely, Olaf Kübler

摘要

We propose a snake-based approach that allows a user to specify only the distant end points of the curve he wishes to delineate without having to supply an almost complete polygonal approximation. This greatly simplifies the initialization process and yields excellent convergence properties. This is achieved by using the image information around the end points to provide boundary conditions and by introducing an optimization schedule that allows a snake to take image information into account first only near its extremities and then, progressively, toward its center. In effect, the snakes are clamped onto the image contour in a manner reminiscent of a ziplock being closed.

论文关键词:Image Processing, Artificial Intelligence, Computer Vision, Computer Image, Convergence Property

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论文官网地址:https://doi.org/10.1023/A:1007924018415