Eigen-deformations for elastic matching based handwritten character recognition

Deformations in handwritten characters have category-dependent tendencies. In this paper, the estimation and the utilization of such tendencies called eigen-deformations are investigated for the better performance of elastic matching based handwritten character recognition. The eigen-deformations are estimated by the principal component analysis of actual deformations automatically collected by the elastic matching. From experimental results it was shown that typical deformations of each category can be extracted as the eigen-deformations. It was also shown that the recognition performance can be improved significantly by using the eigen-deformations for the detection of overfitting, which is the main cause of the misrecognition in the elastic matching based recognition methods.

[1]  Seiichi Uchida,et al.  An Efficient Two-Dimensional Warping Algorithm , 1999 .

[2]  Seiichi Uchida,et al.  Using eigen-deformations in handwritten character recognition , 2002, Object recognition supported by user interaction for service robots.

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

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

[5]  Dinggang Shen,et al.  An Adaptive-Focus Deformable Model Using Statistical and Geometric Information , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Alex Pentland,et al.  Flexible Images: Matching and Recognition Using Learned Deformations , 1997, Comput. Vis. Image Underst..

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

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

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

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

[11]  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).

[12]  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.

[13]  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).

[14]  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..

[15]  Seiichi Uchida,et al.  A monotonic and continuous two-dimensional warping based on dynamic programming , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[16]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

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

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

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

[20]  Anil K. Jain,et al.  Feature extraction methods for character recognition-A survey , 1996, Pattern Recognit..

[21]  Toru Wakahara,et al.  Shape Matching Using LAT and its Application to Handwritten Numeral Recognition , 1994, IEEE Trans. Pattern Anal. Mach. Intell..