DocumentCode :
3308478
Title :
Hybrid thinning through reconstruction
Author :
Doermann, David ; Kia, Omid
Author_Institution :
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Volume :
2
fYear :
1995
fDate :
14-16 Aug 1995
Firstpage :
632
Abstract :
One difficulty with many pixel-wise thinning algorithms is that they produce unacceptable results at junction points, or in the presence of contour noise. The authors present a novel approach to detecting ambiguous regions in a thinned image. The method uses the reconstructability properties of appropriate thinning algorithms to reverse the thinning process and automatically detect those pixels which may have resulted from more then one stroke in the image. The ambiguous regions are then interpreted and reconstructed using domain specific or derived contextual information. The approach has the advantage of using local methods to rapidly identify strokes (or regions) which have been thinned correctly and allowing more detailed analysis based on non-local methods in the remaining regions
Keywords :
edge detection; image reconstruction; image segmentation; noise; ambiguous region detection; automatic pixel detection; contextual information; contour noise; hybrid thinning; image reconstruction; image stroke; junction points; local methods; nonlocal methods; pixel-wise thinning algorithms; Algorithm design and analysis; Automation; Educational institutions; Image reconstruction; Pattern analysis; Pattern recognition; Pixel; Shape; Skeleton; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
Type :
conf
DOI :
10.1109/ICDAR.1995.601975
Filename :
601975
Link To Document :
بازگشت