Contour Detection Method for Electron Beam Spot Based on Random Walk, Active Contour, and Improved B-Spline Curve Fitting

With increasingly wider application of electron beam processing, especially in the field of microfabrication, research on the process, diagnosis, and simulation of electron beam spot has become crucial for further technological advancements. In this paper, to respond to the diagnostic needs of electron beam spots formed during processing, an OpenCV based contour detection algorithm is proposed by means of the analysis and processing of electron beam spot images. The algorithm employs the combination of random walks and the contour extraction algorithm incorporating the Canny operator and targeting weak edge in complex background in particular. Additionally, it introduces an active contour algorithm to handle images with gapped edges. By improving the B-spline curve fitting and optimizing curvature, interference caused by material deformation on the contours is effectively addressed. Ultimately, the algorithm overcame disturbances from gaps and noise and obtains, clear and faithfully restored original contours that closely resemble the actual machining. The algorithm is intended preserve edge information as much as possible and restore the original shape of the target contours. Roundness and homogeneity parameters are collected, and the algorithm’s superiority is validated through quality factor analysis of electron beam spot image results with different edge structures.