Debonding Defect Detection of CFRP Based on Thermal Signal Reconstructed Region Growing Algorithm
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摘要: 提出了基于区域生长和热成像信息重构的融合算法，该算法能较好地解决OPT（光激励红外热成像）方法缺陷检测中分辨率低的难题，显著提高缺陷和非缺陷区域的对比度，实现缺陷的精确检出。为了评价不同算法的检测性能，采用了基于事件的F-score评价方法来衡量检测结果，该方法能定量比较不同特征提取算法。Abstract: In this paper, the fusion of seeded region growing and thermal signal reconstruction algorithm has been proposed to solve the problem of low resolution of defect detection. The algorithm can significantly enhance the contrast ration between defects and sound areas, and realize the accurate positioning of defects. In order to objectively and quantitatively evaluate the detection performance of different algorithms, the event based F-score is computed to measure the detection results.
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