Journal of System Simulation
Abstract
Abstract: Aiming at the problems of large measurement error, single image information, and poor real-time performance in binocular vision ranging, a binocular ranging method based on ORB (oriented fast and rotated brief) features is proposed. Median filtering is performed on the video frame, the ORB feature of the image is extracted, and the Hamming distance with the best matching effect is selected through experiments. The RANSAC (random sample consensus) model estimation is performed on the selected matching points, the mismatches are removed, the model relationship between parallax and true distance is analyzed, the optimal ranging model is constructed and verified on the experimental platform. The results show that the proposed method has the advantages of accurate ranging, fast running speed and strong robustness compared with other binocular ranging methods, and can display the distance information of the features in the image in real time.
Recommended Citation
Yang, Jinghui; Liu, Dekang; Du, Wanhe; and Xing, Lining
(2022)
"Research on Binocular Ranging System Based on Image Features,"
Journal of System Simulation: Vol. 34:
Iss.
3, Article 19.
DOI: 10.16182/j.issn1004731x.joss.20-0793
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss3/19
First Page
624
Revised Date
2021-01-11
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-0793
Last Page
632
CLC
TP391.41
Recommended Citation
Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing. Research on Binocular Ranging System Based on Image Features[J]. Journal of System Simulation, 2022, 34(3): 624-632.
DOI
10.16182/j.issn1004731x.joss.20-0793
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