Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
531879 | Pattern Recognition | 2007 | 14 Pages |
Abstract
In this paper we introduce a new symmetry feature named “symmetry kernel” (SK ) to support a measure of symmetry. Given any symmetry transform SS, SK of a pattern PP is the maximal included symmetric sub-set of PP for all directions and shifts. We provide a first algorithm to exhibit this kernel where the centre of symmetry is assumed to be the centre of mass. Then we prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its symmetric version. That leads to a second algorithm. The associated symmetry measure is a modified difference between the respective surfaces of a pattern and its kernel. A series of experiments supports the actual algorithm validation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Bertrand Zavidovique, Vito Di Gesù,