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An Assessment of Image Matching Algorithms in Depth Estimation
Ashraf Anwar, Ibrahim El Rube
Pages - 109 - 123     |    Revised - 05-04-2013     |    Published - 30-04-2013
Volume - 7   Issue - 2    |    Publication Date - April 2013  Table of Contents
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KEYWORDS
Stereo vision, Image Matching Algorithms, SIFT, SURF, MSER, Correspondence.
ABSTRACT
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
CITED BY (1)  
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Dr. Ashraf Anwar
Taif University - Saudi Arabia
ashrafmanwar90@yahoo.com
Mr. Ibrahim El Rube
College of Computers and Information Technology - Saudi Arabia