Recognition of printed Chinese characters by using Neural Network
Attaullah Khawaja, Shen Tingzhi, Noor Muhammad Memon, Altaf Hussain Rajpar · 2006
The main driving force behind neural network research is the desire to create a machine that works similar to the manner our own brain works. Neural networks have been used in a variety of different areas to solve a wide range of problems. Unlike human brains that can identify and memorize the characters like letters or digits; computers treat them as binary graphics. Therefore, algorithms are necessary to identify and recognize each character. In this article, we are going to look at a method for "printed Chinese character recognition". This article presents a technique for the recognition of printed Chinese characters using back propagation algorithm. A back propagation network consists of at least three layers of units, an input layer, at least one intermediate hidden layer, and an output layer. When a back propagation network is cycled, an input pattern is propagated forward to the output units through the intervening input-to-hidden and hidden-to-output weights. The article also discusses Chinese character recognition using preprocessing, projection and zoning feature extraction. The proposed methodology has been successfully implemented in an experimental recognition system