Handwritten chinese character recognition using eigenspace decomposition

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.