Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Handwritten Chinese Character Recognition: Alternatives to Nonlinear Normalization
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Directional Pattern Matching for Character Recognition Revisited
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global Shape Normalization for Handwritten Chinese Character Recognition: A New Method
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Moment normalization of handprinted characters
IBM Journal of Research and Development
Gabor filters-based feature extraction for character recognition
Pattern Recognition
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The technology of handwritten Chinese character recognition (HCCR) has seen significant advances in the last two decades owing to the effectiveness of many techniques, especially those for character shape normalization and feature extraction. This chapter reviews the major methods of normalization and feature extraction and evaluates their performance experimentally. The normalization methods include linear normalization, nonlinear normalization (NLN) based on line density equalization, moment normalization (MN), bi-moment normalization (BMN), modified centroid-boundary alignment (MCBA), and their pseudo-two-dimensional (pseudo 2D) extensions. As to feature extraction, I focus on some effective variations of direction features: chaincode feature, normalization-cooperated chaincode feature (NCCF), and gradient feature. The features are compared with various resolutions of direction and zoning, and are combined with various normalization methods. In experiments, the current methods have shown superior performance on handprinted characters, but are insufficient applied to unconstrained handwriting.