Adaptive Recognition System of the I1-Pa Stenographic Character Images by Using Line Scan Method and BEP

In this paper, we would study the applicability of neural networks to the recognition process of Korean stenographic character image, applying the classification function, which is the greatest merit of those of neural networks applied to the various pans so far, to the stenographic character recognition, relatively simple classification work. Korean stenographic recognition algorithms, which recognize the characters by using some methods, have a quantitative problem that despite the simplicity of the structure, a lot of basic characters are impossible to classify into a type. They also have qualitative one that it is not easy to classify characters for the delicacy of the character forms. Even though this is the result of experiment under the limited environment of the basic characters, this shows the possibility that the stenographic characters can be recognized effectively by neural network system. In this system, we got 90.86% recognition rate as an average.