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Comparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations
O.S. Seredin 1, O.A. Kushnir 1, S.A. Fedotova 1

1 Tula State University, 300012, Tula, Russia, Lenin Ave 92

 PDF, 1085 kB

DOI: 10.18287/2412-6179-CO-1115

Pages: 921-928.

Full text of article: English language.

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 significant 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.

Citation:
Seredin OS, Kushnir OA, Fedotova SA. Comparative analysis of reflection symmetry detection methods in binary raster images with skeletal and contour representations. Computer Optics 2022; 46(6): 921-928. DOI: 10.18287/2412-6179-CO-1115.

Acknowledgements:
This study was supported by the Russian Science Foundation, Grant No. 22-21-00575, https://rscf.ru/project/22-21-00575/.

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