Handwritten and Machine printed OCR for Geez Numbers Using Artificial Neural Network

TL;DR

This paper develops an OCR system for recognizing handwritten and machine-printed Geez numbers using a feedforward neural network, achieving approximately 89.88% accuracy.

Contribution

It introduces a novel approach for Geez number recognition employing neural networks, addressing a gap in existing Ethiopic script research.

Findings

Achieved ~89.88% classification accuracy

Collected 560 Geez number images from various sources

Demonstrated effectiveness of neural networks for Geez OCR

Abstract

Researches have been done on Ethiopic scripts. However studies excluded the Geez numbers from the studies because of different reasons. This paper presents offline handwritten and machine printed Geez number recognition using feed forward back propagation artificial neural network. On this study, different Geez image characters were collected from google image search and three persons are instructed to write the numbers using pencil. In total we have collected 560 numbers of characters. We have used 460 of the characters for training and 100 are used for testing. Accordingly we have achieved overall all classification ~89:88%