Improvement of artificial neural network based character recognition system, using SciLab

In the proposed work a character recognition system to extract printed text from an image is developed using Kohenen self organizing maps (SOM) based retrieval system. SOM being an unsupervised method of training has a superior feature extracting property. Samples of same characters which are oriented at same angle but with different size, color and fonts are used. After calculation of certain topological and geometrical properties of a character it is classified and recognized. With self organizing map together with K means clustering algorithm using SciLab software, the system has achieved a remarkable accuracy of 99% to 100%, when tested for various text input images.