Multi-font printed amharic character image recognition: Deep learning techniques

Abstract

In this paper, we propose a technique to recognize multi-font printed Amharic character images using deep convolutional neural network (DCNN) which is one of the recent techniques adopted from the deep learning community. Experiments were done on 86,715 Amharic character images with different level of degradation and multiple font types. The proposed method has fewer pre-processing steps and outperforms the standard approach used in classical machine learning techniques. We systematically evaluated the performance of the recognition model and achieved 96.02% of character recognition accuracy.