Research on the algorithm of image feature detection and matching

Jiali Zhang

doi:10.54254/2755-2721/5/20230636

Research Article

Open access

Published on 31 May 2023

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Zhang,J. (2023). Research on the algorithm of image feature detection and matching. Applied and Computational Engineering,5,527-535.

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Research on the algorithm of image feature detection and matching

Jiali Zhang *^,1,

¹ College of Landscape Achitecture, NanJing Forestry University, Nanjing, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/5/20230636

Abstract

In-depth research on feature detection technology affects people's modern life. Modern artificial intelligence can act as the eyes of human beings and efficiently filter out effective information from complex pictures. Corner detection has now evolved into a tool for efficient image scanning. People's increasingly stringent requirements for image processing continue to promote the birth of new technologies. Corner detection methods have been improved and perfected, and have experienced detectors such as Harris, FAST, Scalriant Feature Transform (SIFT), Speeded Up Robust Feature (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), KAZE, AKAZE and Oriented FAST and Rotated BRIEF (ORB). In the face of many mainstream detectors, the main research purpose of this paper is to rely on Python and Computer vision to study the detection efficiency of various detectors in different environments. In this experiment, thirteen groups of pictures were selected, and after being flipped, complicated, and blurred respectively, they were detected by different detectors to obtain the results. Finally, by comparing the feature detection points, detection time and other factors, this study found that the ORB detector can be competent in most situations and is currently the fastest and stable feature point detection and extraction algorithm. On the other hand, the BRISK detector can handle highly blurred images more efficiently.

Keywords

Computer vision, feature detection and matching

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References

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Cite this article

Zhang,J. (2023). Research on the algorithm of image feature detection and matching. Applied and Computational Engineering,5,527-535.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Conference website: http://www.confspml.org

ISBN：978-1-915371-57-7(Print) / 978-1-915371-58-4(Online)

Conference date: 25 February 2023

Editor：Omer Burak Istanbullu

Series: Applied and Computational Engineering

Volume number: Vol.5

ISSN：2755-2721(Print) / 2755-273X(Online)

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