research-article

An Improved ORB Feature Point Matching Algorithm

Authors:

Yang Zhang,

Chao Li,

Chuqing Cao,

Yunfeng GaoAuthors Info & Claims

CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence

Pages 207 - 211

https://doi.org/10.1145/3297156.3297184

Published: 08 December 2018 Publication History

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Abstract

ORB, a very fast binary descriptor based on BRIEF, which is rotation invariant and resistant to noise. To solve the problem that the traditional ORB feature descriptor does not have scale invariance, an improved ORB feature point matching algorithm which borrowing the idea of Binary Robust Invariant Scalable Keypoints (BRISK) algorithm to uniformly sample the extracted feature points is proposed in this paper. The experimental results show that the algorithm not only inherits the advantages of the high speed from ORB algorithm but also has good scale invariance. It is suitable for applications requiring high real-time and large scale changes.

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Akdim KRoukhe ARoukhe H(2024)An Improved RANSAC Method Using Absolute Median Deviation (MAD) Based on Adaptive Threshold2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)10.1109/IRASET60544.2024.10549597(1-6)Online publication date: 16-May-2024
https://doi.org/10.1109/IRASET60544.2024.10549597
Luo FZhang LFan HChen W(2023)An image stabilization method based on adaptive ORB for offshore wind turbine logo image2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)10.1109/ICCECE58074.2023.10135541(57-61)Online publication date: 6-Jan-2023
https://doi.org/10.1109/ICCECE58074.2023.10135541
Zhu YCao ZYang JHou HQuan Y(2023)Fast multi-feature tracking method based on tightly coupled sensorsMeasurement10.1016/j.measurement.2023.113528221(113528)Online publication date: Nov-2023
https://doi.org/10.1016/j.measurement.2023.113528
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Index Terms

An Improved ORB Feature Point Matching Algorithm
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Interest point and salient region detections

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CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence

December 2018

641 pages

ISBN:9781450366069

DOI:10.1145/3297156

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

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Published: 08 December 2018

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CSAI '18: 2018 2nd International Conference on Computer Science and Artificial Intelligence

December 8 - 10, 2018

Shenzhen, China

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Akdim KRoukhe ARoukhe H(2024)An Improved RANSAC Method Using Absolute Median Deviation (MAD) Based on Adaptive Threshold2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)10.1109/IRASET60544.2024.10549597(1-6)Online publication date: 16-May-2024
https://doi.org/10.1109/IRASET60544.2024.10549597
Luo FZhang LFan HChen W(2023)An image stabilization method based on adaptive ORB for offshore wind turbine logo image2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)10.1109/ICCECE58074.2023.10135541(57-61)Online publication date: 6-Jan-2023
https://doi.org/10.1109/ICCECE58074.2023.10135541
Zhu YCao ZYang JHou HQuan Y(2023)Fast multi-feature tracking method based on tightly coupled sensorsMeasurement10.1016/j.measurement.2023.113528221(113528)Online publication date: Nov-2023
https://doi.org/10.1016/j.measurement.2023.113528
Shi MZhang ZZhang WSun WLi Y(2021)Automatic assembly of micro-miniature parts based on coaxial alignment and ORB feature matchingMATEC Web of Conferences10.1051/matecconf/202133602009336(02009)Online publication date: 15-Feb-2021
https://doi.org/10.1051/matecconf/202133602009
Kamel MHussein SSalama GElhalwagy Y(2020)Robust Target Detection in Optical Scene Based on Multiple Reference Images2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)10.1109/NILES50944.2020.9257980(208-212)Online publication date: 24-Oct-2020
https://doi.org/10.1109/NILES50944.2020.9257980
Zhang JLu KLuo K(2020)An improved SLAM algorithm based on feature contour extraction for camera pose estimation2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)10.1109/CISP-BMEI51763.2020.9263661(153-157)Online publication date: 17-Oct-2020
https://doi.org/10.1109/CISP-BMEI51763.2020.9263661
Liu ZGuo YFeng ZZhang S(2019)Improved Rectangle Template Matching Based Feature Point Matching Algorithm2019 Chinese Control And Decision Conference (CCDC)10.1109/CCDC.2019.8833208(2275-2280)Online publication date: Jun-2019
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An ORB Feature Matching Algorithm for Mobile Devices

Image feature point matching method based on improved BRISK

Indoor Scene Classification: A Comparative Study of Feature Detectors and Local Descriptors

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