A method of extracting curvature features and its application to handwritten character recognition

Author

Miura, K.T. ; Sato, R. ; Mori, S.

Author_Institution

Dept. of Mech. Eng., Shizuoka Univ., Hamamatsu, Japan

Volume

2

fYear

1997

fDate

18-20 Aug 1997

Firstpage

450

Abstract

Proposes an orthodox method of extracting curvature features based on a curve fitting approximation. It enables us to obtain analog values of curvatures of a given curve. This means that a so-called gray zone between two categories can be identified and also that very shallow concavities can be detected. For this purpose, cubic B-splines are obtained using a least squares method with natural conditions at the end-points. The method was tested on synthesized noisy data sets such as 2→Z, 4→9 and 1→3. The results are so good that the method can be used to obtain analog features as intended. Demonstrative experimental results are shown for the data set for 1→3

Keywords

curve fitting; feature extraction; handwriting recognition; optical character recognition; splines (mathematics); analogue values; cubic B-splines; curvature feature extraction; curve-fitting approximation; end-point conditions; grey zone; handwritten character recognition; least squares method; shallow concavities; synthesised noisy data sets; Character recognition; Curve fitting; Feature extraction; Humans; Least squares approximation; Mechanical engineering; Optical character recognition software; Shape; Spline; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on

Conference_Location

Ulm

Print_ISBN

0-8186-7898-4

Type

conf

DOI

10.1109/ICDAR.1997.620537

Filename

620537