A new pedestrian detection algorithm based on digital signal processor（ DSP） embedded platform based on electronic image stabilization processing is designed. The smoothing feature trajectory method is used to deal with the electronic image stabilization processing on input video. The Sobel edge operator is used to extract the image of the head and shoulder edge of the human body. According to the improved Hausdorff similarity measurement principle

a pedestrian target detection algorithm based on improved Hausdorff distance headshoulder edge template matching is proposed. The pedestrian target is tracked by Kalman filtering algorithm in realtime. The actual road test results show that pedestrian detection algorithm based on improved Hausdorff distance head-shoulder edge template matching designed and implemented on the TMS320 DM8168 embedded platform can achieve real-time detection and real-time tracking for pedestrians

detection rate of 95 %

the detection speed is 9 frames per second

and error detection rate of 4 % can be achieved

it can meet the demand for actual use.