Development of Handwriting Recognition Using Deep Learning in Unity3D

Handwriting recognition is a technology that recognizes people's written documents, characters written on paper, and characters shown in pictures. Typical technologies include OCR and on-line handwriting recognition technology. OCR had a high recognition rate of writing that was clearly written, but if not, it had a low recognition rate. On-Line handwriting recognition technology clearly differed depending on the difference between handwriting input order and a person's handwriting. In this paper, in order to compensate for these shortcomings, we propose a handwriting recognition system using deep learning. In this paper, the learning data were designed using Convolutional Neural Network and EMNIST data set among neural network algorithms and the whole system was constructed using Unity3D game engine. In this paper, we also did a comparative analysis to see if CPU and GPU performance affect learning results, and although there was no big difference in loss value and acuracy value results, there was a maximum speed difference of 30 times at learning speed. Finally, the results of recognition were analyzed through experiments, and alphabets with similar shapes of characters and numbers, such as O, q, and l, had lower recognition rates. And if the experimenter wrote the characters to look similar to other alphabets, the recognition rate was low. The system proposed in this paper has developed an artificial intelligence system using game engine, so the process procedure has been simplified and the compatibility has improved.