An Assessment of Image Matching Algorithms in Depth Estimation

International Journal of Image Processing

Ibrahim El Rube¹  Ashraf Anwar¹ 

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关键词: Stereo vision;    Image Matching Algorithms;    SIFT;    SURF;    MSER;    Correspondence.;   

DOI  :  

来源: Computer Science Journals

【 摘 要 】

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.

【 授权许可】

Unknown