Off-line Manchu character recognition based on multi-classifier ensemble with combination features
Chen Guang Guo · Jisuanji gongcheng yu sheji · 2012
To improve the off-line Manchu handwritten character recognition rate,a method of recognition based on the multi-classifier of back propagation neural network ensemble with combination features is presented.Firstly,the preprocessing is performed to segment the Manchu character units aiming at Manchu character image.Secondly,it is implemented to recognize the projection feature,chain code one and begin and end point and cross point one of Manchu character unit and the combination features of these ones.Finally,the post processing of Manchu character recognition result is done by the method of hidden Markov model and the recognition rate further is improved.The result of the experiment shows that the recognition rate of the multi-classifier ensemble is higher than the single one and the more features,the better in the multi-classifier ensemble.