DocumentCode :
382353
Title :
A frequency domain algorithm for detection and classification of cyclic and dihedral symmetries in two-dimensional patterns
Author :
Lucchese, Luca
Author_Institution :
Dept. of Electr. & Comput. Eng., Oregon State Univ., Corvallis, OR, USA
Volume :
2
fYear :
2002
fDate :
2002
Abstract :
This paper presents a very effective algorithm for detecting and classifying cyclic and dihedral symmetries from images of finite patterns. Some results concerning reflectional and rotational symmetries of Fourier transforms are presented and exploited to define a convenient frequency domain function whose zero-crossings contain distinctive pairs of orthogonal lines related to the order of the symmetry. The discrimination between cyclic and dihedral symmetries is accomplished by comparing these zero-crossings with those of a second frequency domain function. Several examples of symmetric patterns correctly classified by our algorithm are reported and discussed in the paper.
Keywords :
Fourier transforms; frequency-domain analysis; group theory; image classification; pattern classification; symmetry; Fourier transforms; cyclic groups; cyclic symmetries; dihedral groups; dihedral symmetries; finite patterns; frequency domain algorithm; reflectional symmetries; rotational symmetries; symmetric patterns; symmetry classification; symmetry detection; two-dimensional patterns; zero-crossings; Art; Fourier transforms; Frequency domain analysis; Frequency estimation; Mirrors; Pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-7622-6
Type :
conf
DOI :
10.1109/ICIP.2002.1040070
Filename :
1040070
Link To Document :
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