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A Dual Threshold Calculating Method for Fiber's Edge Extraction

机译:一种用于光纤边缘提取的双阈值计算方法

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In the fiber cross-sectional image analysis system, correctly detecting fiber's edge is critical for fiber geometric feature extraction and further fiber identification. In this paper, a dual threshold calculating method is proposed to obtain accurate and continuous fiber edge, as well as to control the image noise. After eliminating the non-uniform illumination in the fiber image, the low threshold is calculated based on the statistics histogram of the standard deviation of pixels' gray level in the image. And then the high threshold is computed by bisection algorithm combined with the low threshold. After tracing and denoising algorithm, the fiber wall that can correctly describe fiber's contour is detected. The pseudo edges and dual edges detected by traditional algorithms are eliminated, and image noise is well reduced. The experimental result shows that the proposed dual threshold selection algorithm is simple, convenient and efficient to extract fiber edge from fiber cross-sectional image.
机译:在光纤横截面图像分析系统中,正确检测光纤的边缘对于光纤几何特征提取和进一步的光纤识别至关重要。在本文中,提出了一种双阈值计算方法来获得精确和连续的光纤边缘,以及控制图像噪声。在消除光纤图像中的不均匀照明之后,基于图像中像素的灰度级的标准偏差的统计直方图计算低阈值。然后通过与低阈值组合的二分算法计算高阈值。在跟踪和去噪算法之后,检测到可以正确描述光纤轮廓的光纤壁。消除了传统算法检测的伪边缘和双边缘,并且图像噪声很大降低。实验结果表明,所提出的双阈值选择算法简单,方便,有效地从光纤横截面图像中提取光纤边缘。

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