A Tire X-ray Flaw Detection Method Based on Reranking Using Background Features

Abstract

The invention provides a tire X-ray defect detection method for reranking by using background features. When the defect detection is performed after the model is trained, not only the pictures to be detected are input into the model, but also a plurality of pictures without any defects are randomly selected for input. In the model; when feature extraction is performed on the image to be detected, the feature of the corresponding position in the unblemished image is also extracted; then the similarity between the defect feature vector and the background feature vector is calculated, and the candidate frames are re-ranked according to the similarity and then output The final detection results have the following advantages: 1) The tire X-ray defect detection based on deep learning can avoid problems such as low efficiency and high labor costs in the tire quality inspection process caused by human factors; 2) Make full use of the information of flawless pictures, A certain correction is made to the probability of the candidate box.

Description

technical field [0001] The invention relates to the technical fields of computer vision and industrial detection, in particular to a tire X-ray defect detection method using background features for reranking. Background technique [0002] Tires are an important pillar of my country's national economy, and tires in my country can be divided into bias-ply tires and radial-ply tires according to their carcass. Radial tires are widely used due to the advantages of small flow resistance, long service life, and good shock absorption performance. However, radial tires have very high production requirements, and their manufacturing process is more complicated than bias-ply tires. In the production process of radial tires, it is very susceptible to the influence of mechanical equipment, production process and other external environments, and there will be some defects such as impurities, thin tires, air bubbles, etc. These defects will affect the quality of tires and further affect ...

AI Technical Summary

Problems solved by technology

However, radial tires have very high production requirements, and their manufacturing process is more complicated than that of bias tires

In the production process of radial tires, it is very susceptible to the influence of mechanical equipment, production process and other external environments, and there will be some defects such as impurities, thin tires, air bubbles, etc. These defects will affect the quality of tires and further affect the safety of traffic driving

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