Share Email Print
cover

Proceedings Paper

Feature-preserving thinning algorithm for optical character recognition
Author(s): Ting-Shan Cheng; Cheng-Chin Chiang; Shing-Ming Roan; Hsin-Chia Fu
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Thinning is usually regarded as a process of deleting boundary pixels of a character pattern until all strokes are of one pixel in width without deforming the original stroke configuration and connection. Suppose an OCR system uses deformed skeletons as recognition features, we may see that a `T' may erroneously be recognized as a `Y' or `r.' In order to preserve original stroke features, we propose that global attributes should be considered in the thinning procedure. In this paper, we present a new 3 X 3 window-based binary thinning method that considers both local and global attributes in each thinning iteration. We have designed and implemented a fast thinning algorithm to incorporate these two attributes. This algorithm can (1) prevent any excessive removing of pixels at the junction of two strokes or at the end of a stroke, which causes Y-shaped or shortened skeletons, and (2) can detect and remove any spooky type noise (one or two pixels standing on the surface of a stroke) which usually produces spiky skeletons in most of the previously proposed thinning algorithms. Experiment results show that our thinning method can preserve precise skeleton features of the original character patterns.

Paper Details

Date Published: 14 April 1993
PDF: 12 pages
Proc. SPIE 1906, Character Recognition Technologies, (14 April 1993); doi: 10.1117/12.143629
Show Author Affiliations
Ting-Shan Cheng, National Chiao Tung Univ. (Taiwan)
Cheng-Chin Chiang, National Chiao Tung Univ. (Taiwan)
Shing-Ming Roan, National Chiao Tung Univ. (Taiwan)
Hsin-Chia Fu, National Chiao Tung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 1906:
Character Recognition Technologies
Donald P. D'Amato, Editor(s)

© SPIE. Terms of Use
Back to Top