DocumentCode :
1101034
Title :
Symmetry as a continuous feature
Author :
Zabrodsky, Hagit ; Peleg, Shmuel ; Avnir, David
Author_Institution :
Inst. of Comput. Sci., Hebrew Univ., Jerusalem, Israel
Volume :
17
Issue :
12
fYear :
1995
fDate :
12/1/1995 12:00:00 AM
Firstpage :
1154
Lastpage :
1166
Abstract :
Symmetry is treated as a continuous feature and a continuous measure of distance from symmetry in shapes is defined. The symmetry distance (SD) of a shape is defined to be the minimum mean squared distance required to move points of the original shape in order to obtain a symmetrical shape. This general definition of a symmetry measure enables a comparison of the “amount” of symmetry of different shapes and the “amount” of different symmetries of a single shape. This measure is applicable to any type of symmetry in any dimension. The symmetry distance gives rise to a method of reconstructing symmetry of occluded shapes. The authors extend the method to deal with symmetries of noisy and fuzzy data. Finally, the authors consider grayscale images as 3D shapes, and use the symmetry distance to find the orientation of symmetric objects from their images, and to find locally symmetric regions in images
Keywords :
image processing; symmetry; 3D shapes; continuous measure of distance from symmetry; fuzzy data; grayscale images; noisy data; occluded shapes; symmetrical shape; symmetry distance; Chemical processes; Computer science; Gray-scale; Image reconstruction; Medical diagnosis; Mirrors; Noise shaping; Reflection; Retina; Shape measurement;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.476508
Filename :
476508
Link To Document :
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