Glass bottle cap gap width detection combined with transmission lighting system design based on machine vision

Guangmang Cui; Jufeng Zhao; Liyao Zhu; Xiaoli Gong

doi:10.1117/12.2520324

12 March 2019 Glass bottle cap gap width detection combined with transmission lighting system design based on machine vision

Guangmang Cui, Jufeng Zhao, Liyao Zhu, Xiaoli Gong

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Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110230O (2019) https://doi.org/10.1117/12.2520324
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

Combined with the design and construction of transmission lighting system, the machine vision detection scheme is proposed for bottle cap gap width inspection of industrial production line. With the consideration of the reflective properties of glass bottle material, the transmission lighting method using white LED array light source is designed.. It could avoid the disturbance on the detection algorithm caused by the nonuniformity of the imaging region. The vision detection algorithm is developed by using automatic bottle cap region search method and edge detection by seed growing. The upper and bottom edge line position is extracted precisely and the real bottle cap gap width is calculated by image pixel physical size calibration. The real experimental imaging system is setup and the experimental results demonstrate that the presented machine vision detection scheme could realize high precision bottle cap sealing gap width detection with detection precision as 0.01mm. The vision algorithm has high accuracy and the processing speed could satisfy the production line task requirements for bottle cap detection.

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Guangmang Cui, Jufeng Zhao, Liyao Zhu, and Xiaoli Gong "Glass bottle cap gap width detection combined with transmission lighting system design based on machine vision", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110230O (12 March 2019); https://doi.org/10.1117/12.2520324

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KEYWORDS

Detection and tracking algorithms

Light sources and illumination

Machine vision

Glasses

Imaging systems

Algorithm development

Visualization

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