We present part of a vision system for blind and visually impaired people. It detects obstacles on sidewalks and provides guidance to avoid them. Obstacles are trees, light poles, trash cans, holes, branches, stones and other objects at a distance of 3 to 5 meters from the camera position. The system first detects the sidewalk borders, using edge information in combination with a tracking mask, to obtain straight lines with their slopes and the vanishing point. Once the borders are found, a rectangular window is defined within which two obstacle detection methods are applied. The first determines the variation of the maxima and minima of the gray levels of the pixels. The second uses the binary edge image and searches in the vertical and horizontal histograms for discrepancies of the number of edge points. Together, these methods allow to detect possible obstacles with their position and size, such that the user can be alerted and informed about the best way to avoid them. The system works in realtime and complements normal navigation with the cane.
Using computer vision, images are analyzed to detect sidewalk borders and two obstacle detection methods are applied inside a predefined window REF .
OBSTACLE DETECTION AND AVOIDANCE ON SIDEWALKS
VISAPP
Computer Science