Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Non-linear point distribution modelling using a multi-layer perceptron
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Representation and Recognition of Handwritten Digits Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel principal component analysis
Advances in kernel methods
Automatic Construction of 2D Shape Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Complex character decomposition using deformable model
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hybridization of gradient descent algorithms with dynamic tunnelingmethods for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Offline handwritten Chinese character recognition by radical decomposition
ACM Transactions on Asian Language Information Processing (TALIP)
An online Bayesian Ying-Yang learning applied to fuzzy CMAC
Neurocomputing
A Novel Character Recognition Algorithm Based on Hidden Markov Models
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Advanced hough transform using a multilayer fractional fourier method
IEEE Transactions on Image Processing
International Journal of Distance Education Technologies
Pattern Recognition Letters
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Handwritten Chinese characters can be recognized by first extracting the basic shapes (radicals) of which they are composed. Radicals are described by nonlinear active shape models and optimal parameters found using the chamfer distance transform and a dynamic tunneling algorithm. The radical recognition rate is 96.5 percent correct (writer-independent) on 280,000 characters containing 98 radical classes.