Earticle

초록

영어

Stereo matching is to obtain disparity map from two or more images whose pixels existing disparity between each other. Aim at the difficulty of meeting both accuracy and speed when using the adaptive support-weight algorithm, an improved adaptive support-weight sparse region-based algorithm accorded with HVS is proposed. First, improve the traditional support-weight formula, and the support-weight of the points can be calculated according to the improved support-weight formula. Second, the dense disparity map is obtained by sparse region-based matching. Third, left-right consistency check and blocking filling is performed for the obtained disparity map. Finally, median filter is used to remove isolated mismatching points and noise points. Experiment results show that, using the presented method, the matching efficiency is above 90 times faster than that of the adaptive support-weight algorithm proposed by Yoon; and the matching accuracy is 12.34% higher than that of SSD. So the improved algorithm is verified for obtaining accurate disparity map fast and meeting the requirements of system practicability.

목차

Abstract
 1. Introduction
 2. Adaptive Support-weight Algorithm
  2.1. Yoon’s Adaptive Support-weight Algorithm
  2.2. Improved Adaptive Support-weight
 3. Sparse Region Stereo Matching
 4. Disparity Refinement
 5. Improved Stereo Matching Algorithm Process
 6. Experiment and Analysis
 7. Conclusion
 References

키워드

저자

• Di Lu [ College of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China ]
• Xue Lin [ College of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605