Predictive segmentation using multichannel neural networks in Arabic OCR system

Abstract

This article offers an open vocabulary Arabic text recognition system using two neural networks, one for segmentation and another one for characters recognition. The problem of words segmentation in Arabic language, like many cursive languages, presents a challenge to the OCR systems. This paper presents a multichannel neural network to solve offline segmentation of machine-printed Arabic documents. The segmented characters are then used as input to a convolutional neural network for Arabic characters recognition. The accuracy of the segmentation model using one font is 98.9%, while four-font model showed 95.5% accuracy. The accuracy of characters recognition on Arabic Transparent font of size 18 pt from APTI data set is 94.8%.