Fast active contour tracking algorithm based on log-likelihood image segmentation

A fast active contour tracking(ACT) algorithm based on log-likelihood image segmentation has been proposed to solve the scale change problem in the process of target tracking. The algorithm adopts the log-likelihood image segmentation method, which segments images according to their log-likelihood images built based on the color difference between target and background, and the mathematical morphology method, and tracks the target with conventional ACT algorithm combined with Kalman filter. It tracks the target precisely with distinct contour features and stable tracking performance, and can well adapt to the target scale change. The Kalman filter adopted reduces the number of iterations for algorithm convergence through its forecast of the target position, and thus the fast ACT algorithm is about 33% more efficient than the conventional one.