Infrared Technology, Volume. 42, Issue 2, 168(2020)

Feature Point Matching Between Infrared Image and Visible Light Image Based on SIFT and ORB Operators

Shaoli XI1...2, Wei LI1,*, Junfeng XIE2 and Fan MO2 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    References(6)

    [2] [2] Barbara Zitová, Flusser J. Image registration methods: a survey[J]. Image and Vision Computing, 2003, 21(11): 977-1000.

    [9] [9] Lowe David G. Distinctive image features from scale-invariant interest points[J]. International Journal of Computer Vision, 2004, 60(2): 91-100.

    [10] [10] FISCHLER M A, BOLLES R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communication of the ACM, 1981, 24(6): 381-395.

    [11] [11] LAM S K, LIM T C, WU M, et al. Data-path unrolling with logic folding for area-time-efficient FPGA-based FAST corner detector[J]. Journal of Real-Time Image Processing, 2017(1): 1-12.

    [12] [12] CALONDER M, LEPETIT V, STRECHA C, et al. Brief: binary robust independent elementary features[C]//European Conference on Computer Vision, 2010: 778-792.

    [13] [13] QI N X, LI X F,YANG X G, et al. An ORB corner tracking method based on KLT[C]//International Conference on Mechatronics and Intelligent Robotics, 2018: 755-763.

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    XI Shaoli, LI Wei, XIE Junfeng, MO Fan. Feature Point Matching Between Infrared Image and Visible Light Image Based on SIFT and ORB Operators[J]. Infrared Technology, 2020, 42(2): 168

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    Paper Information

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    Received: Mar. 20, 2019

    Accepted: --

    Published Online: May. 12, 2020

    The Author Email: Wei LI (ln_as_lw@163.com)

    DOI:

    CSTR:32186.14.

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