Numerical simulation reveals that optical filters improve object image edge extraction, enhancing recognition.
Subject of study. This study examines optical spatial filters designed based on the Fourier-correlator scheme to control the width of extracted object-image edges. Aim of study. The aim of this study is to determine the influence of different light modes on the properties of object-image edge extraction and, consequently, the possibilities for object recognition and identification. Method. A numerical simulation is performed for a Fourier correlator incorporating a multichannel spatial filter matched to Laguerre–Gaussian modes as well as to Zernike polynomials. The multichannel filter enables the simultaneous generation of several transformed images of the same object in a single plane, each with extracted edges of different widths. Main results. The results show that a set of Laguerre–Gaussian modes and Zernike polynomials can be used as a spatial filter to control the width of extracted object-image edges. Practical significance. These findings indicate the potential for improving object visualization and recognition in machine-vision tasks, including real-time applications. Notably, the multichannel optical element forms transformed images in different diffraction orders within a single focal plane, which is advantageous for static dataset formation without the need to replace or reconfigure the filter.
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Khorin et al. (2025) studied this question.
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