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

Zekun Jing; Changjie Liu; Xinlin Jia; Zixiong Li; Dong Chen

doi:10.1117/12.2550049

12 March 2020 Machine vision based recognition and integrity inspection of printing characters on food package

Zekun Jing, Changjie Liu, Xinlin Jia, Zixiong Li, Dong Chen

Proceedings Volume 11439, 2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems; 114391F (2020) https://doi.org/10.1117/12.2550049
Event: 2019 International Conference on Optical Instruments and Technology, 2019, Beijing, China

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.

Citation Download Citation

Zekun Jing, Changjie Liu, Xinlin Jia, Zixiong Li, and Dong Chen "Machine vision based recognition and integrity inspection of printing characters on food package", Proc. SPIE 11439, 2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 114391F (12 March 2020); https://doi.org/10.1117/12.2550049

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KEYWORDS

Image segmentation

Image processing

Neural networks

Machine vision

Optical character recognition

Defect detection

Image filtering

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