Cited By
View all- Yang HSu XLi BXia CZheng HYang MZhang T(2024)Innovative surface roughness detection method based on white light interference imagesMachine Vision and Applications10.1007/s00138-024-01650-z36:1Online publication date: 23-Dec-2024
Evaluation of grinding surface roughness based on color component difference of image
Authors: 
Huaian Yi, Xinjia Zhao, Jie YangAuthors Info & Claims
Huaian Yi, Xinjia Zhao, Jie YangAuthors Info & ClaimsPages 172 - 175
Abstract
The current machine vision-based measurement of surface roughness of workpiece is mainly the evaluation index of gray image, while ignoring the characteristics of richer color information and strong sensitivity, this paper proposes a kind of information difference index of each color component of image to evaluate the grinding surface roughness. According to the different quality of virtual image of color blocks that are formed on grinding surfaces with different roughness, a reference image and a distortion image are selected, and the difference of each color channel information of the two images is calculated to measure the distortion degree of the image, so as to achieve the purpose of measuring the surface roughness. The experimental results show that the proposed indicators have certain feasibility and the method is simple.
References
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- Evaluation of grinding surface roughness based on color component difference of image
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Published In
November 2019
528 pages
ISBN:9781450361910
DOI:10.1145/3378065
Copyright © 2019 ACM.
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In-Cooperation
- Guilin: Guilin University of Technology, Guilin, China
- Wuhan University of Technology: Wuhan University of Technology, Wuhan, China
- International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 April 2020
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- Short-paper
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- Refereed limited
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ICIIP 2019
ICIIP 2019: 2019 4th International Conference on Intelligent Information Processing
November 16 - 17, 2019
China, China
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Overall Acceptance Rate 87 of 367 submissions, 24%
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View all- Yang HSu XLi BXia CZheng HYang MZhang T(2024)Innovative surface roughness detection method based on white light interference imagesMachine Vision and Applications10.1007/s00138-024-01650-z36:1Online publication date: 23-Dec-2024
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