標題: Multi-linguistic handwritten character recognition by Bayesian decision-based neural networks
作者: Fu, HC
Xu, YY
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
公開日期: 1997
摘要: This paper proposes a multi-linguistic handwritten characters recognition system based on Bayesian decision-based neural networks (BDNN). The proposed system consists of two modules: First, a coarse classifier determines an input character to one of the pre-defined subclasses partitioned from a large character set, such as Chinese mixed with alphanumerics. Then a character recognizer determines the input image to its most matched reference character in the subclass. The proposed BDNN can be effectively applied to implement all these modules. It adopts a hierarchical network structures with nonlinear basis functions and a competitive credit-assignment scheme. Our prototype system demonstrates a successful utilization of BDNN to handwriting of Chinese and alphanumeric character recognition on both the public databases (HCCR/CCL for Chinese and CEDAR for the alphanumerics) and in house database (NCTU/NNL). Regarding the performance, experiments on three different databases all demonstrated high recognition (88 similar to 92%) accuracies as well as low rejection/acceptance (6.7%) rates, as elaborated in Section 3.2. As to the processing speed, the whole recognition process (including image preprocessing, feature extraction, and recognition) consumes approximately 0.27second/character on a Pentium-90 based personal computer, without using hardware accelerator or co-processor.
URI: http://hdl.handle.net/11536/19727
ISBN: 0-7803-4256-9
期刊: NEURAL NETWORKS FOR SIGNAL PROCESSING VII
起始頁: 626
結束頁: 635
Appears in Collections:Conferences Paper