Handwritten numeral recognition using gradient and curvature of gray scale image

In this paper, the authors study on the use of gradient and cur,, attire of the gray scale character image to improve the accuracy of handwritten numeral recognition. Three procedures, based oil Curvature coefficient, bi-quadratic interpolation and gradient vector interpolation, are proposed for calculating the curvature of lie equi-gray Scale Curves of an input image. Then two procedures to compose a feature vector of the gradient and the curvature are described. The efficiency of the feature hectors are tested by recognition experiments for the handwritten numeral database IPTP CDROM1 and NIST SD3 and SD7. The experimental results show the usefulness of the curvature feature and recognition rate of 99.49% and 98.25%, which are one of the highest rates ever reported for these databases (H, Kato et al.. Technical Report of IEICE, PRU95-3, 1995 p. 17 R.A. Wilkinson et al., Technical Report NISTIR 4912, August 1992 J. Geist et al.. Technical Report NISTIR 5452, June 1994), are achieved, respectively. (C) 2002 Pattern Recognition Society, Published by Elsevier Science Ltd. All rights reserved.