Abstract
Aiming to solve the defects detection problems of metal plate fluorescent coating in printing, a machine vision-based metal plate fluorescent coating printing quality online detection system was provided. According to the requirements of factory and measurement accuracy, the camera, lens and illumination mode in the image acquisition module are selected, which forms an imaging effect that is conducive to image processing, and the problem of high-light bright spots and the surrounding object reflections caused by the reflective surface of the coating surface has been solved. Using color space conversion technology, BLOB analysis technology, sub-pixel edge extraction technology and template matching technology to detect common defects that appear on the coating, such as color spots, uneven printing, pattern defects. Under VS2010 environment, based on C# and Halcon, the on-line inspection software system for the printing quality of fluorescent coatings on the metal plate was developed. This software is used to test examples online, the results show that the speed of the provided detection system is quickly and the detection results are reliable, it can meet the requirements of factory.
This project is supported by the National Key R&D Program of China (Grant No. 2018YFB010 4101).
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Wu, Y., Zhao, F., Xin, C., Gao, J., Chen, Z. (2020). Defects Detection System for Fluorescent Coating of Metal Plate Based on Machine Vision. In: Tan, J. (eds) Advances in Mechanical Design. ICMD 2019. Mechanisms and Machine Science, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-32-9941-2_94
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DOI: https://doi.org/10.1007/978-981-32-9941-2_94
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