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Proceedings Paper

Character recognition using a biorthogonal discrete wavelet transform
Author(s): George S. Kapogiannopoulos; Manos Papadakis
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Paper Abstract

We present an approach to off-line optical character recognition for hand-written or printed characters using for feature extraction and classification biorthogonal discrete wavelet transform. Our aim is to optimize character recognition methods independently of printing styles, writing styles and fonts used. Characters are identified with their contours, thus characterized from their curvature function. Curvature function is used for feature extraction while classification is accomplished by LVQ algorithms. This method achieves great recognition accuracy and font insensitivity requiring only a small training set of characters.

Paper Details

Date Published: 23 October 1996
PDF: 10 pages
Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255249
Show Author Affiliations
George S. Kapogiannopoulos, Univ. of Athens (Greece)
Manos Papadakis, Hellenic Military Academy (Greece)


Published in SPIE Proceedings Vol. 2825:
Wavelet Applications in Signal and Image Processing IV
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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