DocumentCode :
2478953
Title :
Linear Decomposition of Planar Shapes
Author :
Faure, Alexandre ; Feschet, Fabien
Author_Institution :
LAIC Lab., Univ. de Clermont, France
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
1096
Lastpage :
1099
Abstract :
The issue of decomposing digital shapes into sets of digital primitives has been widely studied over the years. Practically all existing approaches require perfect or cleaned shapes. Those are obtained using various pre-processing techniques such as thinning or skeletonization. The aim of this paper is to bypass the use of such pre-processings, in order to obtain decompositions of shapes directly from connected components. This method has the advantage of taking into account the intrinsic thickness of digital shapes, and provides a decomposition which is also robust to noise.
Keywords :
image recognition; shape recognition; digital shape decomposition; image recognition; planar shape linear decomposition; skeletonization technique; thinning techniques; Feature extraction; Image segmentation; Junctions; Noise; Pixel; Robustness; Shape; chinese postman problem; digital geometry; triangulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.274
Filename :
5595864
Link To Document :
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