A pentagonal fast block matching algorithm for motion estimation using adaptive search range

In this paper, we present a PFBMA (Pentagonal Fast Block Matching Algorithm) using adaptive search range. The proposed algorithm classifies images into dynamic and static images by a motion equation and performs block matching using adaptive search range. The motion equation calculates the degree of motion in a MB (Macro Block). A MB declared as static by this equation is matched with a small fixed search range and a MB declared as dynamic is estimated with three different search ranges. In this search pattern, more points are allocated in the region of high MV (Motion Vector) probability which is found by smaller matching error and these searching points appear like a pentagonal shape. This proposed pentagonal search pattern also considers search direction to avoid a local minimum. The experimental results show that the proposed algorithm achieves the low computational complexity and better image quality compared with other conventional fast block matching algorithms.