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http://dx.doi.org/10.15207/JKCS.2019.10.10.015

X-ray Image Correction Model for Enhanced Foreign Body Detection in Metals  

Kim, Won (Division of IT Convergence, Woosong University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.10, 2019 , pp. 15-21 More about this Journal
Abstract
X-rays with shorter wavelengths than ultraviolet light have very good penetration power. It is convergence in industrial and medical fields has been used a lot. n particular, in the industrial field, various researches have been conducted on the detection of foregin body inside metal that can occur in the production process of products such as metal using x-ray, a non-destructive inspection device. Detectors are becoming increasingly popular for the popularization of DR (Digital Radiography) photography methods that digitally acquire X-ray video images. However, there are cases where foreign body detection is impossible depending on the sensor noise and sensitivity inside the detector. When producing a metal product, since the defective rate of the produced product may increase due to contamination of the foreign body, accurate detection is necessary. In this paper, we provide a correction model for X-ray images acquired in order to improve the efficiency of defect detection such as foreign body inside metal. When applied to defect detection in the production process of metal products through the proposed model, it is expected that the detection of product defects can be processed accurately and quickly.
Keywords
Convergence; Detector; Image Correction; Image Averaging; Scintillator;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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