A Target Detection Algorithm Based on Histogram Feature and Particle Swarm

It is one challenge to select a general feature for object representation fixed the unconstrained videos. An object detection method which is robust to the target rotation and scales is proposed based on the histogram feature and particle swarm optimization. First, the characters of histogram are presented, and then the merits of histogram feature are analyzed. To cover the computation problem of pixel by pixel searching, particle swarm optimization (PSO) is employed. Then the flowchart of target detection algorithm using histogram and PSO is described. The experimental result proved that the histogram processes the merits of robustness and efficiency for target detection, and that the computation could be improved due to the performance of PSO.