A Modified HOG Algorithm based on the Prewitt Operator

Abstract

The histogram of oriented gradient(HOG) is a feature descriptor used for object detection in the computer vision and image processing, and it is widely used for pedestrian detection. The conspicuous image feature can improve the detective accuracy of the pedestrian detection. In order to improve the conspicuousness of extracted gradient, this paper modifies the gradient extraction operator based on the traditional HOG algorithm. By the tests of different operators, this paper chooses the Prewitt operator to extract the gradient information. Experimental results indicate that the mean and variance of extracted gradient are larger than the gradient of traditional HOG algorithm. The extracted gradient should be generated the conspicuous HOG feature that may improve the performance of pedestrian detection.