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Proceedings Article

Binary adaptive semi-global matching based on image edges

[+] Author Affiliations
Han Hu, Yuri Rzhanov, Philip J. Hatcher, R. D. Bergeron

Univ. of New Hampshire (United States)

Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311D (July 6, 2015); doi:10.1117/12.2196960
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From Conference Volume 9631

  • Seventh International Conference on Digital Image Processing (ICDIP 2015)
  • Charles M. Falco; Xudong Jiang
  • Los Angeles, United States | April 09, 2015

abstract

Image-based modeling and rendering is currently one of the most challenging topics in Computer Vision and Photogrammetry. The key issue here is building a set of dense correspondence points between two images, namely dense matching or stereo matching. Among all dense matching algorithms, Semi-Global Matching (SGM) is arguably one of the most promising algorithms for real-time stereo vision. Compared with global matching algorithms, SGM aggregates matching cost from several (eight or sixteen) directions rather than only the epipolar line using Dynamic Programming (DP). Thus, SGM eliminates the classical “streaking problem” and greatly improves its accuracy and efficiency. In this paper, we aim at further improvement of SGM accuracy without increasing the computational cost. We propose setting the penalty parameters adaptively according to image edges extracted by edge detectors. We have carried out experiments on the standard Middlebury stereo dataset and evaluated the performance of our modified method with the ground truth. The results have shown a noticeable accuracy improvement compared with the results using fixed penalty parameters while the runtime computational cost was not increased. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Han Hu ; Yuri Rzhanov ; Philip J. Hatcher and R. D. Bergeron
" Binary adaptive semi-global matching based on image edges ", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311D (July 6, 2015); doi:10.1117/12.2196960; http://dx.doi.org/10.1117/12.2196960


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