Adjustment of Formal and Casual Handwritten Characters by means of Deep Learning

Abstract

Recently, document digitalization have decreased an oppotunity of handwriting. On the other hand, such tendency enrich handwriting in some special situations. In order to put some thought into handwriting and express personality, people sometimes debate whether character style suits situations especially considering shape and balance. It is difficult to select character style on writing unless they vividly aware of attractive shape of characters. Those are broadly divided into two styles, "formal" and "casual"; the former means characters suit a curriculum vitae, the latter means characters suit private memo. In this study, we have built the system to visualize probabilities of classifying "formal" and "casual" in order to give suggestion about suitable character styles with Convolutional Neural Networks(CNN). Furthermore, we have introduced the function to automatically generate character images in ideal style with Generative Adversarial Networks(GAN).