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

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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 94% in the Canny detector to 80% in our method: the measurable region of the edge tracking was more extensive than that of the Canny detector.