Skeletonization for fuzzy degraded character images

Author

Chen, Shy-Shyan ; Shih, Frank Y.

Author_Institution

Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

5

Issue

10

fYear

1996

fDate

10/1/1996 12:00:00 AM

Firstpage

1481

Lastpage

1485

Abstract

Most skeletonization algorithms are operated on binary images. To avoid information loss and distortion, a topography-based approach is proposed to apply directly on fuzzy or gray scale images. A membership function is used to indicate the degree of membership of each ridge point with respect to the skeleton. Significant ridge points are linked to form strokes of skeleton. Experimental results show that our algorithm can reduce deformation of junction points anti correctly extract the whole skeleton, although a character may be broken into pieces. For merged characters, the breaking positions can be located by searching for the saddle points. A multiple context confirmation is used to increase the reliability of breaking hypotheses

Keywords

character recognition; edge detection; image classification; binary images; breaking hypotheses reliability; breaking positions; experimental results; fuzzy degraded character images; gray scale images; information distortion; information loss; membership function; merged characters; multiple context confirmation; ridge points; saddle points; skeletonization algorithms; topography based approach; unsupervised character classification; Algorithm design and analysis; Brightness; Computer vision; Degradation; Fuzzy sets; Gray-scale; Pixel; Prototypes; Skeleton; Surface topography;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.536896

Filename

536896