Using eigen-deformations in handwritten character recognition

Deformations in handwritten characters have class-dependent tendencies. For example, characters of class "A" are often deformed by global slant transformation and never deformed to be similar to "R". In this paper, the extraction and the utilization of such tendencies called eigen-deformations are investigated for better performance of elastic matching based recognition systems. The eigen-deformations are extracted by the principal component analysis of actual deformations automatically collected by elastic matching. From experimental results it was shown that the extracted eigen-deformations represent typical deformations of each class. It was also shown that the recognition performance can be improved significantly by using the eigen-deformations in detecting overfitting, which often results in misrecognition.

[1]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[2]  Anil K. Jain,et al.  Representation and Recognition of Handwritten Digits Using Deformable Templates , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Oscar E. Agazzi,et al.  Keyword Spotting in Poorly Printed Documents using Pseudo 2-D Hidden Markov Models , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Kazuhiko Yamamoto,et al.  Research on Machine Recognition of Handprinted Characters , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Seiichi Uchida,et al.  Handwritten character recognition using piecewise linear two-dimensional warping , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[6]  Yoshiki Mizukami.  A handwritten Chinese character recognition system using hierarchical displacement extraction based on directional features , 1998, Pattern Recognit. Lett..

[7]  Akira Tomono,et al.  Affine-Invariant Recognition of Gray-Scale Characters Using Global Affine Transformation Correlation , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Fumitaka Kimura,et al.  Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Timothy F. Cootes,et al.  Automatic Interpretation and Coding of Face Images Using Flexible Models , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Roberto Pieraccini,et al.  Dynamic planar warping for optical character recognition , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  Masaki Nakagawa,et al.  An off-line character recognition method employing model-dependent pattern normalization by an elastic membrane model , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[12]  Seiichi Uchida,et al.  Handwritten character recognition using monotonic and continuous two-dimensional warping , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[13]  Seiichi Uchida,et al.  Piecewise linear two-dimensional warping , 1999, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.