Abstract Non-stationary thermal wave imaging is emerging as a reliable alternative procedure due to its depth scanning and defect detection capabilities to assess the integrity of the materials. This investigation proposes a Decision Tree based anomaly detection in Barker Coded Thermal Wave Imaging (BCTWI). It facilitates automatic detection and visualization of anomalies with better spatial accuracy in a single view to help even an inexperienced personnel to easily assess subsurface features.

中文翻译：

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使用巴克编码热波成像的基于决策树的地下分析

摘要 非平稳热波成像由于其深度扫描和缺陷检测能力来评估材料的完整性，正成为一种可靠的替代方法。本研究提出了一种基于决策树的巴克编码热波成像 (BCTWI) 异常检测。它有助于在单个视图中以更高的空间精度自动检测和可视化异常，以帮助即使是没有经验的人员也能轻松评估地下特征。