Template-based online character recognition

Abstract Handwriting is a common, natural form of communication for humans, and therefore it is useful to utilize this modality as a means of input to machines. One well-known method of classifying individual characters or words is template matching. We demonstrate a template-based system for online character recognition where the number of representative templates is determined automatically. These templates can be viewed as representing different styles of writing a particular character. The templates are then used as a reference for efficient classification using decision trees. Overall, our classifier achieves an 86.9% accuracy on a set of 17,928 alphanumeric characters (36 classes; 10 digits and 26 lowercase letters) with a throughput of over 8 characters per second on a 296 MHz Sun UltraSparc.

[1]  Xiaolin Li,et al.  On-line handwritten alphanumeric character recognition using dominant points in strokes , 1997, Pattern Recognit..

[2]  Homayoon Sadr Mohammed Beigi,et al.  Pre-Processing The Dynamics Of On-Line Handwriting Data, Feature Extraction And Recognition , 1996 .

[3]  Isabelle Guyon,et al.  UNIPEN project of on-line data exchange and recognizer benchmarks , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

[4]  Réjean Plamondon,et al.  An evaluation of motor models of handwriting , 1989, IEEE Trans. Syst. Man Cybern..

[5]  Marc Parizeau,et al.  Model-based On-line Handwritten Digit Recognition , 1998 .

[6]  Lionel Prevost,et al.  Automatic allograph selection and multiple expert classification for totally unconstrained handwritten character recognition , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[7]  Robert P. W. Duin,et al.  Experiments with a featureless approach to pattern recognition , 1997, Pattern Recognit. Lett..

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

[9]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[11]  Isabelle Guyon,et al.  On-line cursive script recognition using time-delay neural networks and hidden Markov models , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[12]  Richard M. Schwartz,et al.  On-line cursive handwriting recognition using speech recognition methods , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Anil K. Jain,et al.  Learning Prototypes for On-Line Handwritten Digits , 1998 .

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

[15]  Anil K. Jain,et al.  Learning prototypes for online handwritten digits , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[16]  Lambertus Schomaker,et al.  A Handwriting Recognition System based on the Properties and Architectures of the Human Motor System , 1990 .

[17]  J. Ross Quinlan,et al.  Bagging, Boosting, and C4.5 , 1996, AAAI/IAAI, Vol. 1.

[18]  Ulrich Bodenhausen,et al.  A connectionist recognizer for on-line cursive handwriting recognition , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[19]  Christopher M. Bishop,et al.  Classification and regression , 1997 .

[20]  Richard F. Lyon,et al.  Combining Neural Networks and Context-Driven Search for Online, Printed Handwriting Recognition in the NEWTON , 1998, AI Mag..

[21]  Sharath Pankanti,et al.  An identity-authentication system using fingerprints , 1997, Proc. IEEE.

[22]  Jianying Hu,et al.  Combining High-Level Features with Sequential Local Features for On-Line Handwriting Recognition , 1997, ICIAP.

[23]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[24]  D. Yeung,et al.  Elastic structural matching for recognizing on-line handwritten alphanumeric characters , 1998 .

[25]  Marc Parizeau,et al.  Model-based online handwritten digit recognition , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[26]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .