Abstract

The recognition of Chinese characters has been an area of great interest for many years, and a large number of research papers and reports have already been published in this area. There are several major problems with Chinese character recognition: Chinese characters are distinct and ideographic, the character size is very large and many structurally similar characters exist in the character set. Thus, classification criteria are difficult to generate. This article presents a technique for the recognition of hand-printed Chinese characters using backpropagation algorithm. The article also discusses Chinese character recognition using preprocessing and projection and zoning feature extraction. The system was tested with 100 characters (each character has 160 samples), and it needs 7 output units from the network.

Keywords:
Character (mathematics) Chinese characters Artificial intelligence Computer science Preprocessor Intelligent character recognition Intelligent word recognition Feature (linguistics) Character recognition Pattern recognition (psychology) Document processing Font Projection (relational algebra) Set (abstract data type) Backpropagation Feature extraction Natural language processing Artificial neural network Image (mathematics) Linguistics Mathematics Algorithm

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Citation History

Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology

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