Abstract
The traditional micro image surface defect detection system had slower running speed and less detection precision, which made the detection system operate inefficient and could not meet the requirements of small image surface defect detection. To this end, the optimization design of the micro image surface defect detection system based on machine vision-based big data analysis was carried out. The system design was optimized with MATLAB 7.0 programming environment; MATLAB technology was used to process small images to visualize calculation results and programming; The filtering of the micro image was detected by the method of spatial domain filtering to complete the detection task of the surface defect of the micro image. The design method was validated and the test data showed that the micro image surface defect detection system ran faster and the detection was more precise. The detection accuracy was 92% and the detection quality was high.
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Research and development of fault warning system for transmission equipment based on multi-source image feature matching of UAV(031800KK52160007/GDKJQQ20161094).
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Su, C., Hu, Jl., Hua, D., Cui, Py., Ji, Gy. (2021). Micro Image Surface Defect Detection Technology Based on Machine Vision Big Data Analysis. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 348. Springer, Cham. https://doi.org/10.1007/978-3-030-67874-6_40
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DOI: https://doi.org/10.1007/978-3-030-67874-6_40
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