Tire X-ray defect detection method based on texture comparison

A technology of light detection and edge detection algorithm, applied in image data processing, instrumentation, calculation, etc., can solve problems such as puncture accidents and uneven tire force, and achieve the effect of solving misjudgment problems, reducing pressure, and improving safety.

Active Publication Date: 2019-10-15
杭州盈格信息技术有限公司
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AI Technical Summary

Problems solved by technology

Sparse cords will lead to uneven force on the tire, and in serious cases, it will cause a blowout accident

Method used

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  • Tire X-ray defect detection method based on texture comparison
  • Tire X-ray defect detection method based on texture comparison
  • Tire X-ray defect detection method based on texture comparison

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Embodiment Construction

[0028] In order to describe the present invention more specifically, the present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation examples.

[0029] Such as figure 1 As shown, the example is to detect whether a tire X-ray image has a tire defect, input the X-ray image, and output whether the tire has a tire defect, the specific implementation is as follows:

[0030] (1) Acquire tire X-ray images. This example takes a radial tire as an example. Tires are mainly composed of bead, sidewall, tread and so on.

[0031] (2) Image preprocessing, steps such as figure 2 shown. Use the Canny operator to preprocess the image, extract the edge, that is, the tire cord, and obtain the gradient binary image. The specific algorithm steps of the Canny operator to find the edge point are as follows:

[0032] First, the image is smoothed using a Gaussian filter. Image Gaussian filtering can be realized directly through a...

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Abstract

The invention discloses a tire X-ray defect detection method based on texture comparison. The method comprises the following steps: firstly, obtaining a tire X-ray image; obtaining a gradient binary image of the tire X-ray image by using an edge detection algorithm; obtaining a y coordinate of the cord thread in the obtained gradient binary image; calculating to obtain a sparsest position and a densest position of cord coordinates; obtaining and comparing the y coordinate difference value of the sparsest a cords and the y coordinate difference value of the densest b cords, if the y coordinatedifference value of the b cords at the densest position of the cords is smaller than the y coordinate difference value of the a cords at the sparsest position of the cords, judging that the tire has the thin tire defect, and otherwise, judging that the tire has no thin tire defect. According to the method, low efficiency caused by human factors can be avoided, and the problem of misjudgment is solved to a certain extent, so that the safety of the tire is greatly improved, and the pressure of quality control personnel can be reduced.

Description

technical field [0001] The invention belongs to the technical field of computer vision and industrial detection, specifically, it is a method for detecting whether tires have rare defects based on texture comparison, so that the computer can replace manual detection of common defects in tire X-ray images . Background technique [0002] Taking X-rays of tires belongs to the last quality monitoring stage of the tire manufacturing process. Nowadays, major manufacturers generally adopt a three-shift rotation system to control the quality of this stage. The specific process is that the tires are sent to the X-ray machine channel, and the X-ray machine takes X-ray images of the tires. The quality inspectors see the X-ray images in front of the monitor, and then the quality inspectors will judge whether there is a defect based on the X-rays. , if there is a defect, the current tire will be sent to a special channel for processing, otherwise the tire will enter the next process. A...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/13G06T7/40G01N23/04
CPCG01N23/04G06T7/0004G06T7/40G06T2207/10116G06T7/13
Inventor 范彬彬陈金水丁启元李莹杨颖
Owner 杭州盈格信息技术有限公司
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