Factor analysis thermography for defect detection of panel paintings

IF 3.7 3区 工程技术 Q1 INSTRUMENTS & INSTRUMENTATION Quantitative Infrared Thermography Journal Pub Date : 2021-12-28 DOI:10.1080/17686733.2021.2019658
Kaixin Liu, Kai-Lun Huang, S. Sfarra, Jian-Hua Yang, Yi Liu, Yuan Yao
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引用次数: 19

Abstract

ABSTRACT Active infrared thermography is an important non-destructive testing method used for revealing defect structures in materials. In many applications, thermographic data processing is necessary to extract defect features from a large number of thermal images. This work proposes to use a factor analysis thermography (FAT) method that automatically extracts defect features from thermograms via exploratory factor analysis, in tandem with a fuzzy c-means (FCM) clustering algorithm to segment the defects and background. By means of factor rotation, factor analysis minimises the complexity of factor loadings and makes the results more interpretable. Consequently, the defect information is extracted while large signal-to-noise ratios are obtained. Employing the FCM image segmentation algorithm on factor loading images reduces the interference of background on human visual detection. Additionally, the parameter selection is emphasised and addressed. Experiments on a panel painting illustrate that the proposed method promotes the accuracy and efficiency of thermographic detection of defects, compared with the popular principal component thermography (PCT) method.
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用于面板绘画缺陷检测的因子分析热成像
摘要主动红外热像仪是一种重要的无损检测方法,用于揭示材料中的缺陷结构。在许多应用中,热成像数据处理是从大量热图像中提取缺陷特征所必需的。这项工作提出使用因子分析热成像(FAT)方法,该方法通过探索性因子分析从热图中自动提取缺陷特征,并结合模糊c-均值(FCM)聚类算法来分割缺陷和背景。通过因子轮换,因子分析将因子负载的复杂性降至最低,并使结果更具可解释性。因此,在获得大的信噪比的同时提取缺陷信息。在因子加载图像上采用FCM图像分割算法,减少了背景对人眼视觉检测的干扰。此外,还强调并说明了参数选择。在面板喷漆上的实验表明,与流行的主成分热成像(PCT)方法相比,所提出的方法提高了缺陷热成像检测的准确性和效率。
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来源期刊
Quantitative Infrared Thermography Journal
Quantitative Infrared Thermography Journal Physics and Astronomy-Instrumentation
CiteScore
6.80
自引率
12.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: The Quantitative InfraRed Thermography Journal (QIRT) provides a forum for industry and academia to discuss the latest developments of instrumentation, theoretical and experimental practices, data reduction, and image processing related to infrared thermography.
期刊最新文献
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