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 and 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.
Original language | English (US) |
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Pages (from-to) | 1481-1485 |
Number of pages | 5 |
Journal | IEEE Transactions on Image Processing |
Volume | 5 |
Issue number | 10 |
DOIs | |
State | Published - 1996 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Graphics and Computer-Aided Design