• Laser & Optoelectronics Progress
  • Vol. 58, Issue 22, 2215002 (2021)
Chunjian Hua1、2、*, Rui Pan1、2, and Ying Chen3
Author Affiliations
  • 1School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • 2Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, Wuxi, Jiangsu 214122, China;
  • 3School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • show less
    DOI: 10.3788/LOP202158.2215002 Cite this Article Set citation alerts
    Chunjian Hua, Rui Pan, Ying Chen. Binocular Ranging Method Based on Improved ORB-RANSAC[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2215002 Copy Citation Text show less
    References

    [1] Brown J, Sukkarieh S. Improving monocular depth prediction in ambiguous scenes using a single range measurement[J]. IFAC-PapersOnLine, 52, 355-360(2019).

    [2] Zhang Z Q, Shi W H. Research and implementation of binocular distance measurement system based on improved scale-invariant feature transform algorithm with parallel acceleration[J]. Laser & Optoelectronics Progress, 56, 141502(2019).

    [3] Stefano L D, Marchionni M, Mattoccia S. A fast area-based stereo matching algorithm[J]. Image and Vision Computing, 22, 983-1005(2004).

    [4] Zeglazi O, Rziza M, Amine A et al. A hierarchical stereo matching algorithm based on adaptive support region aggregation method[J]. Pattern Recognition Letters, 112, 205-211(2018).

    [5] Zhu S Q, Wang Z, Zhang X Q et al. Edge-preserving guided filtering based cost aggregation for stereo matching[J]. Journal of Visual Communication and Image Representation, 39, 107-119(2016).

    [6] Lowe D. Distinctive image features from scale-invariant key points[J]. International Journal of Computer Vision, 20, 91-110(2003).

    [7] Bay H, Ess A, Tuytelaars T et al. Speeded-up robust features (SURF)[J]. Computer Vision and Image Understanding, 110, 346-359(2008).

    [8] Rublee E, Rabaud V, Konolige K et al. ORB: an efficient alternative to SIFT or SURF[C]. //2011 International Conference on Computer Vision, November 6-13, 2011, Barcelona, Spain, 2564-2571(2011).

    [9] Yang Y, Xu S X, Fang J Z et al. Location and measurement method of binocular vision based on improved ORB algorithm[J]. Chinese Journal of Sensors and Actuators, 32, 1694-1699(2019).

    [10] Zou B, Zhao X H, Yin Z S. Image feature matching algorithm based on improved ORB[J]. Laser & Optoelectronics Progress, 58, 0210006(2021).

    [11] Cai L C, Ye Y L, Gao X et al. An improved visual SLAM based on affine transformation for ORB feature extraction[J]. Optik, 227, 165421(2021).

    [12] Yang Q N, Ma T L, Yang C K et al. RANSAC image matching algorithm based on optimized sampling[J]. Laser & Optoelectronics Progress, 57, 101104(2020).

    [13] Zhang Q Z, Wang Y. Binocular stereo vision calibration accuracy evaluation using epipolar constraint[J]. Laser & Optoelectronics Progress, 56, 231504(2019).

    [14] Hu L J, Nooshabadi S. High-dimensional image descriptor matching using highly parallel KD-tree construction and approximate nearest neighbor search[J]. Journal of Parallel and Distributed Computing, 132, 127-140(2019).

    [15] Duan Z Y, Wang N, Zhao W Z et al. Sub-pixel edge location algorithm based on Gauss integral curved surface fitting[J]. Chinese Journal of Scientific Instrument, 38, 219-225(2017).

    [16] Liu S D, Xing C C, Zhou G H. Measurement accuracy analysis of binocular vision system in long-distance three-dimensional coordinate measurement[J]. Laser & Optoelectronics Progress, 58, 1415007(2021).

    [17] Fan Y G, Chai J L, Xu M M et al. Improved fast image registration algorithm based on ORB and RANSAC fusion[J]. Optics and Precision Engineering, 27, 702-717(2019).

    [18] Sun H, Wang P. An improved ORB algorithm based on region division[J]. Journal of Beijing University of Aeronautics and Astronautics, 46, 1763-1769(2020).

    Chunjian Hua, Rui Pan, Ying Chen. Binocular Ranging Method Based on Improved ORB-RANSAC[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2215002
    Download Citation