A Neural Network Based Character Recognition System Using Double Backpropagation

Malaysian Journal of Computer Science

S. M. Aziz¹  Joarder Kamruzzaman¹ 

关键词: Neural networks;    backpropagation;    double backpropagation;    character recognition;    Rapid Transform;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: University of Malaya * Faculty of Computer Science and Information Technology

【 摘 要 】

Proposes a neural network based invariant character recognition system using double backpropagation network. The model consists of two parts. The first is a preprocessor which is intended to produce a translation, rotation and scale invariant representation of the input pattern. The second is a neural net classifier. The outputs produced by the preprocessor at the first stage are classified by this neural net classifier trained by a learning algorithm called double backpropagation. The recognition system was tested with ten numeric digits (0~9). The test included rotated, scaled and translated version of exemplar patterns. This simple recognizer with double backpropagation classifier could successfully recognize nearly 97% of the test patterns.

【 授权许可】

Unknown