DocumentCode :
594809
Title :
Accurate junction detection and reconstruction in line-drawing images
Author :
The-Anh Pham ; Delalandre, Mathieu ; Barrat, Sabine ; Ramel, Jean-Yves
Author_Institution :
Lab. of Comput. Sci. (LI), Francois Rabelais Univ., Tours, France
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
693
Lastpage :
696
Abstract :
In this paper, we present an approach for junction detection and reconstruction in line-drawing images. Our approach is shifted to a problem of high curvature point detection from the skeleton of image. Like this, it is independent of any vectorization process and parameter free. The junction reconstruction stage takes benefit of the reliable skeleton segments and their topological relations to reconstruct junctions and make their positions accurate. The experimental results show that the proposed method is competitive with other baseline methods and can achieve accurate junction detection with some pixel errors.
Keywords :
image reconstruction; object detection; accurate junction detection; high curvature point detection; junction reconstruction; line-drawing images; pixel errors; skeleton segments; vectorization process; Detectors; Image reconstruction; Image segmentation; Junctions; Noise; Reliability; Skeleton;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460229
Link To Document :
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