Citation: | Xu Wei, Gu Sen, Chu Chengzhi, et al. Real-time correction of image drift in scanning electron microscope[J]. Opto-Electronic Engineering, 2018, 45(12): 180198. doi: 10.12086/oee.2018.180198 |
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Overview: With the development of nanoscience, new nanomaterials and their excellent properties have been continuously discovered and recognized, showing a broad application prospect. Compared with the traditional optical microscope, the scanning electron microscope (SEM) has been widely used in the characterization of nanomaterials, micro deformation measurement with the advantages of its simple preparation, wide range of adjustable magnification, high resolution and great depth of field. In addition, the use of SEM images as visual sensors has merit in the development of automated nanomanipulations, such as automatic detection of IC chips, automatic pick-up of nanowires, and automatic measurement of nanowire impedance characteristics by four-point probes, making humans liberated from tedious nano-manipulations, greatly improving work efficiency. However, the drift of images caused by electron beam drift and electromagnetic interference at high magnification will affect the size measurement and characterization of nanomaterials in SEM.
At present, domestic and foreign scholars have actively studied the correction method of SEM image drift, but there are still many obvious shortcomings. Cizmar et al. aligned the images correctly to form a single image by using larges of image frames, but which can't meet the requirements of the real-time in SEM. In order to solve the problem of real time, Naresh took the ORB combing the RANSAC to correct the drift image, but it does not eliminate the external points. The increase of the external points lead to the rapid increase of the sampling times of RANSAC, and then affects the efficiency of the algorithm and the accuracy of the measurement. Although AFM compensation algorithm has been able to solve the problem of image drift, it is not suitable for SEM because of the different principles. An image shift correction algorithm based on ORB (oriented FAST and rotated BRIEF) combing the PROSAC (progressive sample consensus) is proposed in this paper. Firstly, the ORB algorithm is used to detect the feature between the reference image and real-time image. Then the initial matching of the feature is implemented by using the Hamming distance and cross-matching. Moreover, the RANSAN (random sample consensus) optimization algorithm PROSAC is used to calculate the homography matrix between frames and the final exact homography matrix is re-iterated after eliminating exterior point. Finally, the SEM image drift is corrected in real time using the perspective transformation of the homography matrix. The experiments show that the proposed algorithm is high precision and satisfies the requirement of SEM real-time processing. This method can meet the requirements of the drift correction in SEM under different magnifications, and provide help for SEM measurement, characterization and other applications.
The working principle of SEM
SEM images at different times
The flow chart of SEM image drift correction
FEI drift correction at 30000× magnification. (a) Reference image; (b) Real-time image; (c) Corrective image
FEI drift correction at 35000× magnification. (a) Reference image; (b) Real-time image; (c) Corrective image
SU8010 drift correction at 30000× magnification. (a) Reference image; (b) Real-time image; (c) Corrective image
SU8010 drift correction at 35000× magnification. (a) Reference image; (b) Real-time image; (c) Corrective image