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Proceedings Paper

Machine vision based recognition and integrity inspection of printing characters on food package
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Paper Abstract

Food packaging bags are fast-moving consumer products with large output and fast production speed. Instant noodle bags need to be printed on the production date and number before packaging the food. For the possible date or code printing error, character sticking, incompleteness, etc., the correctness of the characters cannot be judged in real time by the human eye. A set of automatic recognition characters and detection systems are used to binarize, filter and tilt the picture, and use image morphology and horizontal and vertical projection to segment a single character. BP neural network is used to identify the character and compare it to the template to obtain the degree of defect and compare it with the threshold to determine whether the character is qualified. The detection speed of the system can reach 3 images per second, which can realize real-time recognition and detection of characters, so as to eliminate non-conforming products in time.

Paper Details

Date Published: 12 March 2020
PDF: 10 pages
Proc. SPIE 11439, 2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 114391F (12 March 2020); doi: 10.1117/12.2550049
Show Author Affiliations
Zekun Jing, Tianjin Univ. (China)
Changjie Liu, Tianjin Univ. (China)
Xinlin Jia, Tianjin Univ. (China)
Zixiong Li, Tianjin Univ. (China)
Dong Chen, China Shipbuilding Corp., Ltd. (China)


Published in SPIE Proceedings Vol. 11439:
2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems
Jigui Zhu; Kexin Xu; Hai Xiao; Sen Han, Editor(s)

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