Chinese video characters recognition based on cluster and multi neural network

Author

Li, Wei ; Wang, Junyi

Author_Institution

Sch. of Comput. Sci., Inner Mongolia Univ., Huhhot, China

Volume

3

fYear

2010

Firstpage

1204

Lastpage

1207

Abstract

In this paper we study the problem of Chinese character recognition in video. We propose a series of algorithms on Chinese character division, tracking. Based on them we design a multi-level sorter. Firstly we extract the features of some samples and employ K-means clustering algorithm to carry on I level classification. Secondly, we employ the algorithm of multi back propagation neural network (MBPNN) to classify every category once again and we call it II level classification. Finally, we carry on the experiment and the testing result proves that these algorithms are effectively and recognition rate is higher than conventional back propagation neural network.

Keywords

backpropagation; character recognition; feature extraction; image classification; neural nets; pattern clustering; video signal processing; Chinese character division tracking; Chinese video character recognition; I level classification; feature extraction; k-means clustering algorithm; multibackpropagation neural network algorithm; multilevel sorter design; Artificial neural networks; Character recognition; Classification algorithms; Clustering algorithms; Feature extraction; Indexes; Support vector machine classification; Chinese character segmentation; Chinese character tracking; K-means clustering; back propagation neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5583647

Filename

5583647