Artificial Neural Network Approach to the Development of OCR for Real Life Amharic Documents
Abay Teshager Birhanu, Ramanathan Sethuraman · 2015
Although some developments have been made in recognizing various types of machine-printed, typewritten and handwritten Amharic documents, there is a need to enhance its performance on real-life documents which have a number of artifacts that affect the performance of the recognizer. This paper presents the development of Optical Character Recognition (OCR) for real life Amharic degraded documents. For classifying the features generated, an Artificial Neural Network (ANN) approach is implemented.The neural network is trained with eight samples taken from real-life documents. The performance of the developed system is tested with documents taken from real-life documents. Accordingly, an average recognition rate of 96.87% for the test sets from the training sets and 11.40% recognition rate is observed for the new test sets.