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