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Cigarette appearance online detection method and device

A detection method and technology for cigarettes, which are used in measurement devices, optical testing of flaws/defects, material analysis by optical means, etc., can solve the problem that cigarettes are prone to misjudgment, appear on two images at the same time, and cannot be identified. Droplets and other problems, to achieve the effect of ensuring the consistency of the entrance feeling

Active Publication Date: 2020-05-22
BEIJING FOCUSIGHT TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] 1. The existing on-line inspection systems for cigarette appearance based on machine vision technology all use area array CCD cameras, and the collected cigarette end face images are two-dimensional plane information, which cannot realize the problem of end face cavity depth (three-dimensional information) defect detection, and The existing detection system can only realize the defect detection of the circumferential surface or the end surface, and has the disadvantage of single function
[0003] 2. The existing on-line inspection system for cigarette appearance based on machine vision technology can only reduce the droplet interference, but cannot identify the droplet and eliminate the interference.
However, when the droplets are in the overlapping position of the field of view of the two cameras, the droplets will appear on the two images at the same time, causing misjudgment
[0004] 3. The existing online cigarette appearance inspection system based on machine vision technology uses image comparison algorithms to detect defects. Since each cigarette is at a different angle on the roller, the position of the collected image with logos or patterns will also change. , using a comparison algorithm to detect patterned cigarettes is likely to cause misjudgment, so the existing comparison algorithm cannot realize defect detection in the area of ​​patterned cigarettes

Method used

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  • Cigarette appearance online detection method and device
  • Cigarette appearance online detection method and device
  • Cigarette appearance online detection method and device

Examples

Experimental program
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Effect test

Embodiment 1

[0114] In this embodiment, the comparison algorithm of the existing cigarette appearance online detection system cannot realize the defect detection of the patterned cigarette area, and the method of eliminating droplets can only reduce the interference of droplets, but cannot identify droplets and eliminate interference. problem, the specific method is as follows:

[0115] S1: The third camera component collects 1,000 images of no defects on the circumferential surface, images of droplets, images of damaged defects, images of stains, and images of foam defects, totaling 5,000 images, which are divided into training sets and prediction sets at a ratio of 4:1;

[0116] S2: Use the threshold segmentation algorithm to separate the background to obtain the cigarette image, and then correct the cigarette image through template matching to ensure that the cigarette is in the same position and direction of each image;

[0117] S3: Divide each image into three sections, namely cigaret...

Embodiment 2

[0124] This embodiment is an alternative solution for using a deep learning model to detect defects on the appearance of the end face of the cigarette holder. The specific implementation method is as follows:

[0125] S1: Collect 1,000 images of non-defective cigarettes on the end face, images of droplet interference, images of roundness defects, images of damage defects, images of stain defects, and images of foam defects, a total of 6,000 images, which are divided into training set and training set at a ratio of 4:1. prediction set;

[0126] S2: Use the threshold segmentation algorithm to separate the background to obtain the mouthpiece image, and calculate the center position of the mouthpiece image, and further determine the region of interest (Region of interest, ROI) of the mouthpiece to be detected;

[0127] S3: Build the GoogLeNet model under the Caffe platform, bring the ROI of the 6 types of images in the training set into the GoogLeNet model for training, and use th...

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Abstract

The invention relates to cigarette appearance detection, in particular to a cigarette appearance online detection method and device. The method comprises the following steps of: S1, respectively collecting a three-dimensional information image of a cigarette holder end surface cavity, a cigarette holder end surface appearance image and a cigarette circumferential surface appearance image at corresponding positions of a cigarette making machine; S2, transmitting the collected images to an image processor to be processed as follows in the specification; and S3, judging the product as a good product or bad product after the images in step 2 are processed by the image processor, and when the product is judged as a bad product, sending a signal to a rejecting controller by the image processor to enable the rejecting controller to act, thus rejecting the bad cigarette. A deep learning model used in the invention can accurately classify defects, and can provide information for manufacturers to eliminate mechanical faults and improve production schemes.

Description

technical field [0001] The invention relates to cigarette appearance inspection, in particular to an online inspection method and device for cigarette appearance. Background technique [0002] 1. The existing on-line inspection systems for cigarette appearance based on machine vision technology all use area array CCD cameras, and the collected cigarette end face images are two-dimensional plane information, which cannot realize the problem of end face cavity depth (three-dimensional information) defect detection, and The existing detection system can only realize the defect detection of the circumferential surface or the end surface, and has the disadvantage of single function. [0003] 2. The existing on-line inspection system for cigarette appearance based on machine vision technology can only reduce the droplet interference, but cannot identify the droplet and eliminate the interference. The existing method of eliminating droplet interference is to install two cameras wi...

Claims

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Application Information

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IPC IPC(8): G01N21/88
CPCG01N21/8851G01N2021/8854G01N2021/8887
Inventor 王岩松方志斌和江镇杨清鉴石海军
Owner BEIJING FOCUSIGHT TECH
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