An Improved Camshift Algorithm Based on Grabcut with a LBP Model of Correction Tracking Centroid

Abstract

According to the analysis of advantages and disadvantages of traditional Camshift algorithm, it can be known that background noise and interference of similar color objects will have a greater impact on Camshift algorithm, which may cause tracking errors easily. This paper presents an improved Camshift algorithm based on Grabcut and LBP centroid tracking correction model. Current frame image enhanced by enhanced coefficient, the Camshift algorithm will apply Grabcut object segmentation to achieve pure histogram for target object and then move the centroid which has been distracted due to similar color objects’ obstacles to uncovered parts of the target object by using LBP centroid tracking correction model. As a result, the problems caused by background noise and similar color obstacles distraction can be solved effectively. Tests presented in the paper can prove that the algorithm can be used to operate the real-time tracking much more steadily and accurately.