An intelligent depth-based obstacle detection system for visually-impaired aid applications

Abstract

In this paper, we present a robust depth-based obstacle detection system in computer vision. The system aims to assist the visually-impaired in detecting obstacles with distance information for safety. With analysis of the depth map, segmentation and noise elimination are adopted to distinguish different objects according to the related depth information. Obstacle extraction mechanism is proposed to capture obstacles by various object proprieties revealing in the depth map. The proposed system can also be applied to emerging vision-based mobile applications, such as robots, intelligent vehicle navigation, and dynamic surveillance systems. Experimental results demonstrate the proposed system achieves high accuracy. In the indoor environment, the average detection rate is above 96.1%. Even in the outdoor environment or in complete darkness, 93.7% detection rate is achieved on average.