Kernel snakes: non-parametric active contour models

TitleKernel snakes: non-parametric active contour models
Publication TypeConference Papers
Year of Publication2003
AuthorsAbd-Almageed W, Smith CE, Ramadan S
Conference NameIEEE International Conference on Systems, Man and Cybernetics, 2003
Date Published2003/10//
ISBN Number0-7803-7952-7
KeywordsActive contours, Artificial intelligence, Bayes methods, Bayesian decision theory, Bayesian methods, decision theory, Deformable models, Image edge detection, Image segmentation, Intelligent robots, Kernel, kernel snakes, Laboratories, multicolored target tracking, nonparametric active contour models, nonparametric generalized formulation, nonparametric model, nonparametric statistics, nonparametric techniques, real time performance, Robot vision systems, statistical pressure snakes, target tracking

In this paper, a new non-parametric generalized formulation to statistical pressure snakes is presented. We discuss the shortcomings of the traditional pressure snakes. We then introduce a new generic pressure model that alleviates these shortcomings, based on the Bayesian decision theory. Non-parametric techniques are used to obtain the statistical models that drive the snake. We discuss the advantages of using the proposed non-parametric model compared to other parametric techniques. Multi-colored-target tracking is used to demonstrate the performance of the proposed approach. Experimental results show enhanced, real-time performance.