Open AccessAn improved algorithm for disparity estimation of SGM stereo matching based on edge detection
Author(s) -
Jian Zhang,
Jing Huang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2010/1/012037
Subject(s) - matching (statistics) , artificial intelligence , algorithm , parallax , computer science , enhanced data rates for gsm evolution , set (abstract data type) , computer vision , blossom algorithm , stereopsis , stereo image , data set , pattern recognition (psychology) , mathematics , image (mathematics) , statistics , programming language
In the fields of depth measurement and computer vision, generating sufficiently accurate disparity maps through various stereo matching algorithms is an important foundation. The SGM semi-global matching algorithm is one of the best stereo matching algorithms, But its filling accuracy is poor in the invalid parallax area. Therefore, on the original basis, an improved algorithm of SGM stereo matching disparity filling based on edge detection is proposed. The experiment uses a standard data set to verify the algorithm. The results show that compared with the original SGM stereo matching algorithm, the paper algorithm can achieve better disparity estimation results in the invalid disparity area.