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ЖУРНАЛЫ // Компьютерная оптика // Архив

Компьютерная оптика, 2022, том 46, выпуск 6, страницы 921–928 (Mi co1087)

ОБРАБОТКА ИЗОБРАЖЕНИЙ, РАСПОЗНАВАНИЕ ОБРАЗОВ

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

Аннотация: 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.

Ключевые слова: binary raster image, reflection symmetry, Jaccard measure, Fourier descriptor

Поступила в редакцию: 24.02.2022
Принята в печать: 14.09.2022

Язык публикации: английский

DOI: 10.18287/2412-6179-CO-1115



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