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The HOG feature has a good description of the pedestrian profile, but the pedestrian detection based on the HOG feature has the problems of slow detection speed and high missed detection rate, which makes the practical application of the algorithm limited. In this paper, aiming at the problem of slow detection rate and high missed detection rate, a pedestrian detection algorithm based on PHOG features is proposed. Firstly, the PHOG feature is proposed. This feature enhances the gradient features in the cell and increases the gradient distribution difference between the target and the background so that the target can be easily learned and identified by the classifier. Then, a method of constructing characteristic pyramid is proposed, and the PHOG features are effectively reduced in dimension, which greatly reduces the detection time. The experimental results show that the proposed PHOG-PCA feature reduces the missed detection rate from 35% to 22% and the detection speed is faster than some popular algorithms.