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Study on Feature Point Matching for Diverse Workpieces Based on an Improved Speeded Up Robust Features(SURF) Algorithm Cover

Study on Feature Point Matching for Diverse Workpieces Based on an Improved Speeded Up Robust Features(SURF) Algorithm

Open Access
|Jun 2026

Authors

Wenjing Liu

nkd_lwj@imust.edu.cn

Inner Mongolia University of Science & Technology, School of Mechanical Engineering, Inner Mongolia Province, China
State Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology, Democracy Road, Qingshan District, China

Yue Ma

prongs@foxmail.com

Inner Mongolia University of Science & Technology, School of Mechanical Engineering, Inner Mongolia Province, China
Inner Mongolia Key Laboratory of Intelligent Diagnosis and Control of Mechatronic Systems, China

Chongwei Tan

a1234565552025@outlook.com

State Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology, Democracy Road, Qingshan District, China

Ben Niu

2845550624@qq.com

Shanxi Aerospace Tsinghua Equipment Co, LTD, No. 266, Changzhi City, China

Petrishin Grigory

petrishingrig@gmail.com

Sukhoi State Technical University of Gomel:Homyel, Republic of Belarus

Shaofeng Wang

Shaofengwang2025@qq.com

Inner Mongolia University of Science & Technology, School of Mechanical Engineering, Inner Mongolia Province, China
Inner Mongolia Key Laboratory of Intelligent Diagnosis and Control of Mechatronic Systems, China

Yanjie Xu

m7894561231998@outlook.com

State Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology, Democracy Road, Qingshan District, China
DOI: https://doi.org/10.30657/pea.2026.32.31 | Journal eISSN: 2353-7779 | Journal ISSN: 2353-5156
Language: English
Page range: 381 - 394
Submitted on: Feb 6, 2026
Accepted on: Jun 1, 2026
Published on: Jun 23, 2026
In partnership with: Paradigm Publishing Services

© 2026 Wenjing Liu, Yue Ma, Chongwei Tan, Ben Niu, Petrishin Grigory, Shaofeng Wang, Yanjie Xu, published by Quality and Production Managers Association
This work is licensed under the Creative Commons Attribution 4.0 License.