Title :
Linear Decomposition of Planar Shapes
Author :
Faure, Alexandre ; Feschet, Fabien
Author_Institution :
LAIC Lab., Univ. de Clermont, France
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;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.274