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Machine vision based liquid level sub-quality product marking method

A marking method and qualified product technology, applied in engine lubrication, machines/engines, instruments, etc., to achieve high detection efficiency, high accuracy, and novel detection methods

Inactive Publication Date: 2016-10-26
TIANJIN UNIV
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  • Abstract
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Problems solved by technology

[0007] The purpose of the present invention is to overcome the shortcomings of manual detection and the limitations of liquid level detection, and provide an efficient method for marking unqualified glass bottle liquid level products based on machine vision

Method used

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  • Machine vision based liquid level sub-quality product marking method
  • Machine vision based liquid level sub-quality product marking method
  • Machine vision based liquid level sub-quality product marking method

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Embodiment Construction

[0023] The present invention will be further described below in conjunction with the accompanying drawings and specific examples.

[0024] see figure 1 , a system device for marking unqualified beverage bottle liquid level based on machine vision, which is divided into 6 modules in terms of function, namely conveyor belt 1, image acquisition module 2, photoelectric trigger 3, lighting module 4, image processing and recognition 5 and output control device 6. The above-mentioned image acquisition module 2 uses a 1.2 million-pixel CCD camera, the lighting module 4 uses an LED backlight board, and the image processing and recognition module 5 uses an industrial computer. The output control device consists of a nozzle controlled by a solenoid valve. The conveyor belt 1 transports the bottle to be tested to the photographing station, and the photoelectric trigger device 3 is used to detect whether the bottle arrives at the photographing position, so as to generate a pulse signal a...

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Abstract

The invention relates to a machine vision based liquid level sub-quality product marking method. The method includes: placing a certain qualified glass bottle at a work station to be tested, acquiring a template for subsequent matching treatment; conveying a glass bottle to be tested to a shooting work station through a conveying belt, and shooting an image of the liquid level of the glass bottle to be tested; performing binarization processing on the image after pretreatment; matching a bottle cap by using a geometric matching method, and detecting a position of the bottle cap; establishing a coordinate system; setting an area-of-interest ROI of a liquid level qualified area; matching a liquid level line by using the geometric method; and determining a sub-quality glass bottle. The machine vision based liquid level sub-quality product marking method is simple in algorithm, is fewer in steps, can achieve rapid detection of images, is high in detection efficiency, cannot be affected by environments, and is high in accuracy rate.

Description

technical field [0001] The invention relates to a glass bottle liquid level detection unqualified marking method, which belongs to the field of machine vision. Background technique [0002] In industrial production lines such as beverages and beer, most of them use manual visual inspection to check whether the bottles are qualified. [0003] Especially in filling production, whether the liquid level of bottled beverages is consistent and whether the height is uniform has a huge impact on the enterprise in the market. However, manual inspection has many defects such as slow speed, low efficiency, unstable inspection quality, [0004] Omissions or false detections often occur, resulting in unstable product quality. Once defective products are produced, it will cause waste. Aiming at the above-mentioned defects of manual detection, the research on bottle cap detection based on machine vision and the establishment of a detection system based on the platform of optical imaging,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01F23/00G01N21/90
CPCG01F23/00G01N21/90
Inventor 刘影吕辰刚郭玺丁珏杨嘉琛米岩陈德胜
Owner TIANJIN UNIV
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