Modelling and simulation of active contour model for object tracking

An active contour models for object tracking using prior contour are investigated. The proposed algorithm uses edge with color feature for tracking and also uses the prior contour information for robust characteristics. The orthogonal search to contour extends search range and reduces computational burden compared with conventional snake algorithms. The conventional algorithms have many problem for tracking, so model based techniques are noticed in tracking with snake. The tracking with models such as eigenvector model and dynamic model are suggested. But they need complex procedures such as training, estimation and matching. The proposed algorithm suggests the tracking scheme such like Kass's one, energy minimization. But it uses the prior contour as a model defining smooth similarities with two contours. The algorithm searches normally and uses dynamic programming to solve energy minimization problem. The main drawbacks of conventional snake algorithm - shrinking, limited search range, sensitive to noises - improved with the proposed algorithm. The external energy using color is also introduced. It can be adopted in robocup to detect ball or patch-tracking application because of the ability to be able to use shape and color information in the same time.