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Proceedings Paper

Hierarchical approach to build a compact character recognition system
Author(s): Xueping Liu
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Paper Abstract

This paper proposes a hierarchical approach to build a compact character recognizing system by reducing the redundancy in dictionaries used to match a hand-written sample with its corresponding code. An elemental stroke dictionary and a character dictionary are used. An algebraic describing method of curves is adopted to divide all the strokes into several classes according to their quasi-topological features (convexity, loop, and connectivity) and geometric ones (size, orientation angle, and position in character, etc.). An elemental stroke is extracted statistically from each class so divided. Based on these elemental strokes, a character category is represented by the numbers of stroke and the types of elemental strokes. To recognize a hand-written character, we find out the type of elemental stroke for each stroke in the character at first, and then we identify the category of the input data by matching the types of elemental stroke with those in the character dictionary.

Paper Details

Date Published: 23 March 1994
PDF: 7 pages
Proc. SPIE 2181, Document Recognition, (23 March 1994); doi: 10.1117/12.171131
Show Author Affiliations
Xueping Liu, Ricoh Co., Ltd. (Japan)

Published in SPIE Proceedings Vol. 2181:
Document Recognition
Luc M. Vincent; Theo Pavlidis, Editor(s)

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