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Machine vision-based glass bottle liquid level detection method

A liquid level detection and machine vision technology, applied in the field of glass bottle liquid level detection, achieves the effect of simple algorithm, wide application range and few steps

Inactive Publication Date: 2016-08-17
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to overcome the shortcomings of manual detection and the limitations of liquid level detection, and provide a simple and efficient glass bottle liquid level detection method based on machine vision

Method used

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  • Machine vision-based glass bottle liquid level detection method
  • Machine vision-based glass bottle liquid level detection method
  • Machine vision-based glass bottle liquid level detection 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 glass 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 and ...

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Abstract

The invention relates to a machine vision-based glass bottle liquid level detection method which comprises the following steps: placing a certain qualified glass bottle at a station to be detected, and collecting a template for subsequent matching treatment; after the glass bottle to be detected arrives at a shooting station through a conveying belt, shooting a liquid level image of the glass bottle; binarizing the preprocessed image; matching a bottle cover through a geometric matching method to detect the position of the bottle cover; establishing a coordinate system; setting a region of interest (ROI) of a liquid level-qualified region; matching a liquid level line through the geometric matching method. An algorithm used in the machine vision-based glass bottle liquid level detection method is simple, and the number of steps is small; quick detection based on the image is realized, and the detection efficiency is high; the influence caused by the environment is less, and the accuracy is high.

Description

technical field [0001] The invention relates to a glass bottle liquid level detection 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, image acquisition, ...

Claims

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Application Information

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IPC IPC(8): G01F23/00G06T7/00
CPCG01F23/00G06T7/0004
Inventor 吕辰刚刘影郭玺杨嘉琛丁珏米岩陈德胜
Owner TIANJIN UNIV
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