Abstract
Computer vision is the area of imitation of biological vision system using computer algorithms and technologies. One of the main usages of this innovative technology is for navigation. Some of the cardinal and challenging parts in navigation are recognition of safe routes and distinguishing them from obstacles. In this paper an innovative algorithm is described and developed for this purpose. This algorithm can be utilized in camera based electronic travel aid (ETA) devices or autonomous vehicles. Furthermore, the focus here is to use this algorithm in an ETA device for helping visually impaired person (VIP). Different methods and techniques can be used in order to develop such an algorithm. Here, the algorithm is designed in a way that generates depth map using block matching technique and process it using Random Sample Consensus (RANSAC) with extra criteria obtained from Inertial Measurement Unit (IMU) in order to extract the ground plane and discover the obstacles. Finally, the algorithm is implemented in a prototype and several experiments are performed in order to measure the process time and success rate.
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