Recognition of Reference Micromarks Images against the Background of Similar Relief Elements

• Published in: Technical physics 2023-10, Vol.68 (10), p.287-291
• Main Author: Gulyaev, P. V.
• Format: Article
• Language: English
• Subjects: Algorithms; Classical and Continuum Physics; Criteria; Equipment and supplies; Histograms; Hough transformation; Image processing; Marking; Mathematical analysis; Parameters; Physics; Physics and Astronomy; Segments; Structural analysis; Substrates
• ISSN: 1063-7842; 1090-6525
• DOI: 10.1134/S106378422470018X

The problem of recognizing a reference micromarking from microscopic images containing pseudo-marking element (similar to the real marking of the substrate relief elements) is considered. The scope of such marking is the identification of the studied or modified surface areas as well as the lines connecting these areas with macroscopic landmarks on the surface. The micromarking is formed using a probe microscope cantilever or a nanoindentor. Examples of images with pseudo-marking elements and the results of their recognition by low-level structural analysis methods previously used for micromarking recognition are given. In particular, a surface curvature detector is used, which has proven itself well in discrete micromarking recognition. The effect of pseudo-marking is the formation of a large number of background key points, which reduce the effectiveness of recognition. The application of the linear Hough transform for approximation and subsequent recognition of separate marking elements is described. It is also shown that to recognize the marks obtained by the probe microscope cantilever, it is advisable to use morphological erosion before the Hough transformation. The procedure for setting the parameters of this transformation, which affect the recognition of markings most significantly, is described. The range of recorded Hough transform segments and the Hough transform threshold are used as such parameters. An image processing algorithm and a recognition evaluation criterion are presented. In this case, a histogram of the distribution of the angles of mutual rotation of the segments detected by the Hough transform is used. The recognition criterion is the presence of dominant peaks with certain values in this histogram. The results showing the efficiency of the presented algorithm are presented.