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首页> 外文期刊>Infrared physics and technology >Defects' geometric feature recognition based on infrared image edge detection
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Defects' geometric feature recognition based on infrared image edge detection

机译：基于红外图像边缘检测的缺陷几何特征识别

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摘要

Edge detection is an important technology in image segmentation, feature extraction and other digital image processing areas. Boundary contains a wealth of information in the image, so to extract defects' edges in infrared images effectively enables the identification of defects' geometric features. This paper analyzed the detection effect of classic edge detection operators, and proposed fuzzy C-means (FCM) clustering-Canny operator algorithm to achieve defects' edges in the infrared images. Results show that the proposed algorithm has better effect than the classic edge detection operators, which can identify the defects' geometric feature much more completely and clearly. The defects' diameters have been calculated based on the image edge detection results.
机译：边缘检测是图像分割，特征提取和其他数字图像处理领域中的一项重要技术。边界在图像中包含大量信息，因此在红外图像中提取缺陷的边缘可以有效地识别缺陷的几何特征。本文分析了经典边缘检测算子的检测效果，提出了模糊C-均值聚类-Canny算子算法来实现红外图像中缺陷的边缘检测。实验结果表明，与经典的边缘检测算子相比，该算法具有更好的识别效果，可以更加完整，清晰地识别出缺陷的几何特征。缺陷直径是根据图像边缘检测结果计算得出的。

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