Matching Algorithm and Parallax Extraction Based on Binocular Stereo Vision

  • Gang LiEmail author
  • Hansheng Song
  • Chan Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 670)


By using binocular stereoscopic vision and planar images, this paper details the process of obtaining 3D information for interested objects and obtains the world and pixel coordinates of any point on the object. The main contents of this article are focus on camera calibration, image correction, stereo matching, and parallax extraction. Furthermore, various algorithms and implementation methods are studied and analyzed. Finally, by comparing correction and stereo matching algorithms, more effective correction algorithm and matching algorithm are achieved.


Binocular stereo vision Calibration algorithm Correction algorithm Stereo matching algorithm Disparity map 



The work described in this paper was funded by The Project of Shaanxi Provincial Science and Technology Program (2014JM8351). And it was also funded by Fundamental Research Funds for the Central Universities of China (2013G1241109).


  1. 1.
    DING Hong-wei, CHAI Ying, LI Kui-fang A fast binocular vision stereo matching algorithm [J]. Acta Optia Sinica, 2009, 29 (8).Google Scholar
  2. 2.
    Yue Ming, Qiuqi Ruan. Face Stereo Matching and Disparity Calculation in Binocular Vision System [C]. 2010 2nd International Conference on Industrial and Information Systems, 2010.Google Scholar
  3. 3.
    YANG Xing-fang, YOU Mei, GAO Feng, YANG Xin-gang, HAN Xu-sha.A new algorithm for corner detection of checkerboard image for camera calibration [J]. Chinese Journal of Scientific Instrument, 2011.Google Scholar
  4. 4.
    Zhang Zheng You. A Flexible Camera Calibration by Viewing a Plane from Unknown Orientations [A], ICCV99 [C], 1999.Google Scholar
  5. 5.
    Yang Xiaomei, three-dimensional image of the correction algorithm [D], Xi’an University of Technology, March 2010.Google Scholar
  6. 6.
    Zhang Huan, Amway, Zhang Qiang, etc. SGBM algorithm and BM algorithm analysis [J]. Surveying and mapping and spatial geographic information, 2016, 39 (10).Google Scholar
  7. 7.
    Jaco Hofmann, Jens Korinth, and Andreas Koch. A Scalable High-Performance Hardware Architecture for Real-Time Stereo Vision by Semi-Global Matching [C], 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016.Google Scholar
  8. 8.
    Heiko Hirschmuller. Accurate and Efficient Stereo Processing by Semi-Global Matching and mutual Information [M]. IEEE, 2005.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Information EngineeringChang’an UniversityXi’anChina

Personalised recommendations