Recognition of Arabic Handwritten Literal Amounts Using Deep Convolutional Neural Networks.

In this paper, we propose using a convolutional neural network (CNN) in the recognition of Arabic handwritten literal amounts. Deep convolutional neural networks have achieved an excellent performance in various computer vision and document recognition tasks, and have received increased attention in the few last years. The domain of handwriting in the Arabic script specially poses a different type of technical challenges. In this work we focus on the recognition of handwritten Arabic literal amount with a limited lexicon. Our experimental results demonstrate the high performance of the proposed CNN recognition system compared to traditional methods.