Research on Automatic Detection Algorithm for Pedestrians on the Road Based on Image Processing Method

Accurate detection of pedestrian targets can effectively improve the performance level intelligent transportation and surveillance projects. In order to enhance accuracy detecting on road, this paper first introduced traditional target algorithm, proposed faster recurrent convolutional neural network (RCNN) algorithm detect targets, improved it make good use features at different scales. Finally, support vector machine (SVM), Faster RCNN, optimized RCNN algorithms were compared by simulation experiments. The results showed that had higher recall rate, obtained a more accurate localization frame, detected than SVM algorithms; frame algorithm.