热成像
人工智能
大津法
分割
计算机视觉
计算机科学
图像分割
二值图像
像素
图像处理
模式识别(心理学)
材料科学
红外线的
图像(数学)
光学
物理
作者
Seungju Lee,Yoonjae Chung,Chunyoung Kim,Wontae Kim
标识
DOI:10.1016/j.infrared.2023.104900
摘要
The infrared thermography (IRT) technique is a highly reliable and attractive technique that can evaluate a large area in real-time without destroying the inspection object. This study used the line scanning method (LSM)-based induction thermography (IT) technique among active IRT to detect thinning defects in S275 steel specimens. Unlike the dynamic mode, LSM was applied to perform sequence processing so that the copper coil shape was removed in the 2D thermal images processed. After image segmentation, a binary image was acquired using the Otsu algorithm. By utilizing image segmentation, the applied threshold for each defect is different when performing the Otsu algorithm. This makes it possible to compare defect detection according to the presence or absence of image Segmentation. Automatic defect detection was performed using a Boundary Tracking algorithm, and 12 defect detections were confirmed. Accuracy was evaluated through pixel calculation, and defects in A, B, and D columns showed high detection accuracy. This study presented the principle of LSM in which includes the relative movement between the IR camera and the specimen. In addition, a mechanism to increase the number of defects detected through image segmentation was presented.
科研通智能强力驱动
Strongly Powered by AbleSci AI