Title :
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
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;
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
DOI :
10.1109/ICDAR.1997.620537
