Highly real-time blind sidewalk recognition algorithm based on boundary tracking

Abstract

In order to solve the problem that existing blind sidewalk recognition algorithms have bad real-time performance, a highly real-time blind sidewalk recognition algorithm based on boundary tracking is proposed, mainly including accurate recognition and tracking recognition. First, accurate recognition step mainly calculates gray level co-occurrence matrix of the initial frame, and uses clustering and Hough transform to find the boundary lines of blind sidewalk in image. Then tracking recognition step takes over next frame. The location of blind sidewalk’s boundary in previous frame is used to predict the small-scale region of interest (ROI) of the boundary in current frame, and boundary lines in that region are extracted based on gray gradient feature. After that, the algorithm checks up the validity of tracking by estimating the consistency of color distribution on both sides of the boundary in previous and current frames: tracking is considered to be valid if the consistency is high, and tracking recognition step continues, otherwise accurate recognition step restarts. In many experiments, the time of accurate recognition and tracking recognition in each image frame under normal illumination are about 0.8 s and 0.1 s, respectively, and the average time of recognition per frame decreases significantly while the recognition rate of blind sidewalk is more than 90%. Meanwhile, the adaptability is good in shadow environment. Experimental results indicate that the algorithm can significantly enhance the real-time performance of blind sidewalk recognition in the premise of ensuring the recognition rate.