Handwritten Digit Recognition Using Encryption Methods

Abstract

Over the past years, deep learning techniques has had a strong impact on many areas of technical intelligence, including handwriting recognition. Handwriting recognition it is defined as the domain which allow a computer to interpret intelligible handwritten inputs from different sources. It is plays an important role in many areas, such as authenticating bank checking, exchanging remote computer files, and document duration. In this paper, we present a novel handwritten digit recognition method based on deep learning. In order to improve the performance of recognizing handwritten digits, we have proposed a new data augmentation method by using different encrypted digit images and image fusion techniques. The experimental results based on the CVL database shown that the proposed method achieved higher accuracy rates that were compared to the state of the art.