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Image Edge Enhancement Detection Method of Human-Computer Interaction Interface Based on Machine Vision Technology

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Abstract

Aiming at the problems of low detection accuracy and long detection time of existing image edge detection technologies, an image edge detection method of human-computer interaction interface based on machine vision technology is proposed. Based on machine vision technology, the image weight is calculated by iterative repeated weighted least square method, the image is Gaussian filtered by improved Canny algorithm, and the optimal threshold is calculated by iterative method to judge the effective edge. Through comparative experiments, it is proved that the maximum detection accuracy of the man-machine interface image edge enhancement detection method based on machine vision technology proposed in this paper is 100%, the detection time is always kept below 0.2S, and the fastest detection time is 0.1 s, which has wide applicability.

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Acknowledgements

This job is supported by Supported by Natural Science Foundation of Shaanxi Province (No.2021JM-344) and Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data (No.IPBED7); Subproject of National Vocational Education Course Resource Library (Intelligent Control Technology Course Resource Library-Virtual Reality Application Technology); Program of Philosophy and Social Science Research of Jiangsu University (No.2017SJB1406); Program of Suzhou Educational Science “Thirteenth Five-Year Plan” (No.16000Z090); The Innovation and Entrepreneurship Training Program for University Students of Jiangsu Province (No.201911054011Y); Program of Modern Education Technology in Jiangsu Province (No.2017-R-54025); Research Project of China Society of Electronic Education 2016 (No.CESEZ2016-86); Educational Reform Project of Suzhou Vocational University (No.SZDJG-18021); Jiangsu Open University”13th Five-Year” scientific research project (No.19TXYB-05). Science and Technology Project of Suzhou under Grant SS202151, Program to Cultivate Middle-aged and Young Cadre Teacher of Suzhou Vocational University, Suzhou.

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Yi Jin provided the algorithm and experimental results, wrote the manuscript, Wei Wei revised the paper, supervised and analyzed the experiment.

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Correspondence to Wei Wei.

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The authors have no relevant financial or non-financial interests to disclose.

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Jin, Y., Wei, W. Image Edge Enhancement Detection Method of Human-Computer Interaction Interface Based on Machine Vision Technology. Mobile Netw Appl 27, 775–783 (2022). https://doi.org/10.1007/s11036-021-01908-0

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