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Cites:

Information Journal Paper

Title

A solution to detect the defect of the cords in the tire in X-ray images

Pages

  49-58

Abstract

 Diagnosing tire defects is an important part of the tire inspection automation process. Various solutions have been proposed to diagnose tire defects using tissue and local information. These solutions are very important in identifying various types of tire quality control defects for tire manufacturing companies. Due to the fact that the examination of X-ray images by the operator is a time-consuming and costly process, so the use of machine vision and machine learning is an important issue in this industry. In this paper, a new solution to detect tire defects in X-ray images based on image processing techniques and using the method of extracting image texture properties is presented. In the proposed method, local binary pattern ( LBP) techniques are used to extract the defect properties. In order to evaluate the proposed solution, the tire data set was prepared with X-ray images, which by applying the proposed algorithm on this set, a good accuracy in fault diagnosis was obtained, which also has a desirable performance.

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  • Cite

    APA: Copy

    SEDAGHAT, Y., PARHIZGAR, N., & KESHAVARZ, A.. (2021). A solution to detect the defect of the cords in the tire in X-ray images. IRANIAN RUBBER MAGAZINE, 26(103 ), 49-58. SID. https://sid.ir/paper/1044048/en

    Vancouver: Copy

    SEDAGHAT Y., PARHIZGAR N., KESHAVARZ A.. A solution to detect the defect of the cords in the tire in X-ray images. IRANIAN RUBBER MAGAZINE[Internet]. 2021;26(103 ):49-58. Available from: https://sid.ir/paper/1044048/en

    IEEE: Copy

    Y. SEDAGHAT, N. PARHIZGAR, and A. KESHAVARZ, “A solution to detect the defect of the cords in the tire in X-ray images,” IRANIAN RUBBER MAGAZINE, vol. 26, no. 103 , pp. 49–58, 2021, [Online]. Available: https://sid.ir/paper/1044048/en

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