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