Skeleton Revision Algorithm Using Maximal Circles

Authors:
Affiliations:
Venue:
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Year:
1998

Citing 6
Cited 0

Computer processing of line images: a survey

Pattern Recognition
Handprinted symbol recognition system

Pattern Recognition
Stroke segmentation by Bernstein-Be´zier curve fitting

Pattern Recognition
Continuous Skeletons from Digitized Images

Journal of the ACM (JACM)
Use of the Hough transformation to detect lines and curves in pictures

Communications of the ACM
Chain of circles for matching and recognition of planar shapes

IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

Thinning is a fundamental concept of computer processing of line images, and it plays an important role in pattern recognition. Most of existing thinning algorithm have a problem to produce distorted skeletons. Some methods to correct the distorted skeleton have been proposed until now, but we can not say they produced complete results. In order to solve the problem, we propose an improved thinning algorithm, which is Skeleton Revision Algorithm using Maximal Circles (SRAMCs). SRAMCs is a hybrid algorithm and the processing route is divided into three stages: (i) thinning using Hilditch algorithm, (ii) removal of spurious pixels using Maximal Circle(MC), (iii) skeleton reconstruction. The results of experiments indicates that SRAMCs would be useful for detection of lines and curves in digitized line images.