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IMAGE PROCESSING, PATTERN RECOGNITION
Comparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations
O. S. Seredin, O. A. Kushnir, S. A. Fedotova Tula State University
Abstract:
The study is a comparative analysis of two fast reflection symmetry axis detection methods: an algorithm to refine the symmetry axis found with a chain of skeletal primitives and a boundary method based on the Fourier descriptor. We tested the algorithms with binary raster images of plant leaves (FLAVIA database). The symmetry axis detection quality and performance indicate that both methods can be used to solve applied problems. Neither method demonstrated any sig-nificant advantage in terms of accuracy or performance. It is advisable to integrate both methods for solving real-life problems.
Keywords:
binary raster image, reflection symmetry, Jaccard measure, Fourier descriptor
Received: 24.02.2022 Accepted: 14.09.2022
Citation:
O. S. Seredin, O. A. Kushnir, S. A. Fedotova, “Comparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations”, Computer Optics, 46:6 (2022), 921–928
Linking options:
https://www.mathnet.ru/eng/co1087 https://www.mathnet.ru/eng/co/v46/i6/p921
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