Paper
14 April 1993 Feature-preserving thinning algorithm for optical character recognition
Ting-Shan Cheng, Cheng-Chin Chiang, Shing-Ming Roan, Hsin-Chia Fu
Author Affiliations +
Proceedings Volume 1906, Character Recognition Technologies; (1993) https://doi.org/10.1117/12.143629
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States
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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ting-Shan Cheng, Cheng-Chin Chiang, Shing-Ming Roan, and Hsin-Chia Fu "Feature-preserving thinning algorithm for optical character recognition", Proc. SPIE 1906, Character Recognition Technologies, (14 April 1993); https://doi.org/10.1117/12.143629
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Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Optical character recognition

Distortion

Binary data

Computer architecture

Computer science

Computing systems

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