Handwritten Numeral Recognition Using Gradient and Curvature of Gray Scale Image

Authors:
Yoshiharu Fujisawa;Meng Shi;Tetsushi Wakabayashi;Fumitaka Kimura
Affiliations:
-;-;-;-
Venue:
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Year:
1999

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Abstract

In this paper, the authors study on the use of curvature in addition to the gradient of the gray scale character image to improve the accuracy of handwritten numeral recognition. Three procedures, based on curvature coefficient, bi-quadratic interpolation and gradient vector interpolation, are proposed for calculating the curvature of the equi-grayscale curves of an input image. The efficiency of the feature vector is tested by recognition experiments for the handwritten numeral database IPTP CDROM1. The experimental result shows the usefulness of the curvature feature and recognition rate of 99.40%, which is the highest one ever reported for the database, is achieved.