Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (23): 219-225.DOI: 10.3778/j.issn.1002-8331.2104-0353

• Graphics and Image Processing • Previous Articles     Next Articles

Research on Stereo Matching Algorithm Based on Multi-feature Fusion and Adaptive Aggregation

CHANG Yawen, ZHAO Dongqing, SHAN Yanhu   

  1. School of Instruments and Electronics, North University of China, Taiyuan 030051, China
  • Online:2021-12-01 Published:2021-12-02



  1. 中北大学 仪器与电子学院,太原 030051


Aiming at the low matching accuracy of local stereo matching in illumination distortion and weak texture areas, a stereo matching algorithm based on cost calculation of multi-feature fusion and adaptive cross window aggregation is proposed. Firstly, the HSV color space component is introduced, combined with the improved Census transform and gradient information to calculate the matching cost, which eliminates the influence of the parallax boundary abnormal value, and enhances the algorithm’s robustness to illumination distortion. Secondly, an adaptive window cost aggregation method based on gradient information and variable color threshold is proposed to improve the matching accuracy of weak texture areas. Finally, the final disparity result is obtained by multi-step disparity refinement. Experimental results show that, compared with AD-Census algorithm, the mismatching rate of proposed algorithm is reduced by 3.24% under the same illumination exposure conditions. It can effectively solve the problem of mismatching parallax boundary and weak texture region, and has good robustness to illumination distortion and can effectively suppress noise interference.

Key words: machine vision, stereo matching, multi-feature fusion, adaptive window, radiometric distortion



关键词: 机器视觉, 立体匹配, 多特征融合, 自适应窗口, 光照失真