Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of handprinted Chinese characters using Gabor features
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
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IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Holistic cursive word recognition based on perceptual features
Pattern Recognition Letters
Text search for medieval manuscript images
Pattern Recognition
Handwritten Chinese character recognition: effects of shape normalization and feature extraction
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Orientation histograms for face recognition
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
A statistical-topological feature combination for recognition of handwritten numerals
Applied Soft Computing
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Directional features have been successfully used forthe recognition of both machine-printed and handwrittenKanji characters for the last decade. This paper attemptsto explain why the directional features are effective. First,the advances of directional features and related methodsare briefly reviewed. Then the properties that thesimilarity measure should hold are discussed andsimulation experiments of directional pattern matchingare conducted to validate the properties. This analysis isexpected to inspire the design of new and more effectivefeatures.