PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Long H., Zhang X., Kuruoglu E. E. Handwritten chinese character recognition using eigenspace decomposition. Technical report, 2012.
 
 
Abstract
(English)
In this paper, we mainly describe a new approach of Handwritten Chinese Character Recognition (HCCR), which is based on eigen-character extraction. The procedure of the eigen-character extraction method is explained including initialization, eigen character extraction (or eigen spaces generation) and character recognition. Two different methods are presented to do eigen character recognition respectively. Besides, k Nearest Neighbor (kNN) is implemented to improve the recognition rate of the new approach. In the end, a comparison is made between the eigen-character extraction approach and other existing approaches through simulation based experiments. The results show that our approach has a satisfying rate and could be further improved if combined with some other methods such as elastic matching and wavelet methods.
Subject Handwriting recognition
Chinese character recognition
Eigenspace decomposition
Eigencharacters
I.5.4 PATTERN RECOGNITION. Computer Vision
I.5.1 PATTERN RECOGNITION. Models
I.5.1 PATTERN RECOGNITION. Statistical
62H25 Factor analysis and principal components
62H35 Image analysis


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