Joint Histogram Between Color and Local Extrema Patterns for Object Tracking

In this paper, a new algorithm meant for object tracking application is proposed using local extrema patterns (LEP) and color features. The standard local binary pattern (LBP) encodes the relationship between reference pixel and its surrounding neighbors by comparing gray level values. The proposed method differs from the existing LBP in a manner that it extracts the edge information based on local extrema between center pixel and its neighbors in an image. Further, the joint histogram between RGB color channels and LEP patterns has been build which is used as a feature vector in object tracking. The performance of the proposed method is compared with Ning et al. on three benchmark video sequences. The results after being investigated proposed method show a significant improvement in object tracking application as compared to Ning et al.