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Computer Optics, 2019, Volume 43, Issue 3, Pages 434–445
DOI: https://doi.org/10.18287/2412-6179-2019-43-3-434-445
(Mi co663)
 

This article is cited in 9 scientific papers (total in 9 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Comparison of binary feature points descriptors of images under distortion conditions

E. A. Krasnabayeua, D. V. Chistobayeub, A. L. Malysheva

a Vitebsk State University named after P.M. Masherov, Vitebsk, Belarus
b Design Bureau “Display”, Vitebsk, Belarus
References:
Abstract: The article is devoted to the review and analysis of binary descriptors of feature points of objects in digital images under distortion conditions. An overview of the BRIEF, ORB, BRISK, FREAK, AKAZE, LATCH methods is given. The evaluation of properties of the descriptors on sample images is performed. The paper addresses problems of using these methods for real time image processing.
Keywords: digital image processing, pattern recognition, image analysis, feature detection, feature description, feature matching.
Received: 19.01.2018
Accepted: 10.04.2019
Document Type: Article
Language: Russian
Citation: E. A. Krasnabayeu, D. V. Chistobayeu, A. L. Malyshev, “Comparison of binary feature points descriptors of images under distortion conditions”, Computer Optics, 43:3 (2019), 434–445
Citation in format AMSBIB
\Bibitem{KraChiMal19}
\by E.~A.~Krasnabayeu, D.~V.~Chistobayeu, A.~L.~Malyshev
\paper Comparison of binary feature points descriptors of images under distortion conditions
\jour Computer Optics
\yr 2019
\vol 43
\issue 3
\pages 434--445
\mathnet{http://mi.mathnet.ru/co663}
\crossref{https://doi.org/10.18287/2412-6179-2019-43-3-434-445}
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  • https://www.mathnet.ru/eng/co663
  • https://www.mathnet.ru/eng/co/v43/i3/p434
  • This publication is cited in the following 9 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    References:21
     
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