SnakesActiveContourModels：主动轮廓模型，蛇.doc

PAGE 11 Snakes: Active Contour Models Michael Kass, Andrew Witkin, and Dimitri Terzopoulos Jonathan Chappelow Biocontrols, Modeling and Computation Spring 2005 Model Overview and Literature Review This paper describes a system defined by a very specific energy minimization criteria used for reaching local minima corresponding to a model of an edge or subjective contour in an image. While edge and contour detection has an expansive literature base, deterministic modeling of contours and shapes makes up a much more limited area of research. In addition, modeling contours using energy-minimizing splines, as described in this paper, comprises a very unique approach to the modeling problem. Unlike parametric shape models which are defined by explicit equations of shape [10], active contours are geometric models in which their coordinates are the parameters of the model. This research is unique in that they have developed an entirely new system for modeling image contours, and they provide an efficient and flexible numerical solution for the system. As will be described, active contours have become an invaluable base tool for segmentation and object tracking. The energy minimization system developed here differs from traditional contour modeling approaches, which typically involved edge detection followed by subjective interpretation and edge connection [1]. The majority of previous edge detection techniques did not employ deterministic system for modeling contours. Simple edge detection merely involves the use of linear operators such as the Laplacian, followed by thresholding or the use of Canny edge selection or similar algorithms [8]. The Hough transform has also been used for shape detection and general image characterization. Towards the goals of image segmentation and understanding, many techniques have been employed, such as k-means, optical flow, and region growing [6, 7]. These methods, however, are limited in their inability to recognize and incorp