A Mobile-Based Obstacle Detection Method: Application to the Assistance of Visually Impaired People

Visual impairments suffer many difficulties when they navigate from one place to another in their daily life. The biggest problem is obstacle detection. In this work, we propose a new smartphone-based method for obstacle detection. We aim to detect static and dynamic obstacles in unknown environments while offering maximum flexibility to the user and using the least expensive equipment possible. Detecting obstacles is based on the analysis of different regions of video frames and using a new decision algorithm. The analysis uses prediction model for each region that generated by a supervised learning process. The user is notified about the existing of an obstacle by alert message. The efficiency of the work is measured by many experiments studies on different complex scenes. It records low false alarm rate in the range of [0.2% to 11 %], and high accuracy in the range of [86% to 94 %].