Abstract
The Navigation and Control Group, Missile Guidance Directorate, Research Development & Engineering Center of the U.S. Army Missile Command is conducting a program to develop and demonstrate a robust, low cost machine vision system for autonomous vehicles. This machine vision system has the requirement of providing robust classification of roads and obstacles over varying terrain, lighting, and weather. The focus of the development is to operate using a passive sensor suite of a color video camera and a black hot FLIR video camera. Machine vision algorithms have been developed and tested in a simulation environment using test sequences from video segments of various road types. This paper presents a novel approach to road and obstacle classification based on color video input. The paper begins by defining the problem and is followed by a discussion of the major functions of the simulation including the mission supervisor, the image server, the image processing algorithms, and concludes with experimental results.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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