An Improved Stereo Vision Image Processing for Object Distance Measurement

Abstract

Humans have the ability to roughly estimate the distance of objects because of stereo vision of the human’s eyes In this thesis we propose an improved stereo vision system to accurately measure the distance of objects in real world Object distance is very useful for obstacle avoidance and navigation of autonomous vehicles The object measurement of stereo camera is better than a single camera and the theory was proposed in many previous researches Recent researches have used stereo cameras for different applications such as 3D image construction distance measurement and occlusion detection The proposed measurement procedure is a three-phase process: object detection segmentation and distance calculation In distance calculation we proposed a new algorithm to reduce the error The result shows our measurement system is capable of providing objects distance with less than 5% measurement error

Date of Award	2014 Jan 17
Original language	English
Supervisor	Ta-Chung Wang (Supervisor)