|
Active contour model, also called snakes, is a framework in computer vision for delineating an object outline from a possibly noisy 2D image. The snakes model is popular in computer vision, and snakes are greatly used in applications like object tracking, shape recognition, segmentation, edge detection and stereo matching. A snake is an energy minimizing, deformable spline influenced by constraint and image forces that pull it towards object contours and internal forces that resist deformation. Snakes may be understood as a special case of the general technique of matching a deformable model to an image by means of energy minimization. In two dimensions, the active shape model represents a discrete version of this approach, taking advantage of the point distribution model to restrict the shape range to an explicit domain learned from a training set. Snakes do not solve the entire problem of finding contours in images, since the method requires knowledge of the desired contour shape beforehand. Rather, they depend on other mechanisms such as interaction with a user, interaction with some higher level image understanding process, or information from image data adjacent in time or space. ==Motivation== In computer vision, contour models describe the boundaries of shapes in an image. Snakes in particular are designed to solve problems where the approximate shape of the boundary is known. By being a deformable model, snakes can adapt to differences and noise in stereo matching and motion tracking. Additionally, the method can find Illusory contours in the image by ignoring missing boundary information. Compared to classical feature attraction techniques, snakes have multiple advantages: * They autonomously and adaptively search for the minimum state. * External image forces act upon the snake in an intuitive manner. * Incorporating Gaussian smoothing in the image energy function introduces scale sensitivity. * They can be used to track dynamic objects. The key drawbacks of the traditional snakes are * They are sensitive to local minima states, which can be counteracted by simulated annealing techniques. * Minute features are often ignored during energy minimization over the entire contour. * Their accuracy depends on the convergence policy.〔Snakes: an active model,Ramani Pichumani,http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/RAMANI1/node31.html〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Active contour model」の詳細全文を読む スポンサード リンク
|