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Object size measurement method from noisy SEM images by utilizing scale space

机译:利用尺度空间从嘈杂的SEM图像中测量物体尺寸的方法

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摘要

We proposed an object size measurement method from noisy scanning electron microscope (SEM) images with shot noise by utilizing the scale space approach. The proposed measurement algorithm consists of six steps: (1) specifying an object to be measured, (2) estimating the noise level, (3) constructing Gaussian and gradient scale spaces, (4) determining a starting scale for edge tracking, (5) edge tracking and (6) object size measurement. For the object size measurement, the model parameters of SEM images are estimated from regions segmented by edge positions at the finest scale. Then the appropriate scale for the object size measurement is automatically selected by estimated model parameters and an optimal scale parameter for smoothing filter in the Canny edge detector. And then, the object size is measured. We applied the algorithm to model SEM images and an SEM image. Though the processing time for our proposed method took about 13 times longer than that of the Canny detector, the range of the probability of extracting true edge positions was extended from 94percent in the Canny detector to 80percent in our method: the measurable region of the edge tracking was more extensive than that of the Canny detector.
机译:我们提出了一种利用尺度空间方法从带有散粒噪声的噪声扫描电子显微镜(SEM)图像中测量物体尺寸的方法。提出的测量算法包括六个步骤:(1)指定要测量的对象;(2)估计噪声水平;(3)构造高斯和梯度标度空间;(4)确定边缘跟踪的起始标度;(5 )边缘追踪和(6)物体尺寸测量。对于物体尺寸的测量,SEM图像的模型参数是从按边缘位置分割的区域中以最佳比例估计的。然后,通过估计的模型参数和用于Canny边缘检测器中的平滑滤波器的最佳比例参数,自动选择适合对象尺寸测量的比例。然后,测量物体的尺寸。我们将算法应用于SEM图像和SEM图像。尽管我们提出的方法的处理时间比Canny检测器要长13倍,但提取真实边缘位置的概率范围从Canny检测器中的94%扩展到了我们方法中的80%:边缘的可测量区域跟踪比Canny探测器更广泛。

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