Handwritten Devanagari Character Generation Using Deep Convolutional Generative Adversarial Network

Abstract

As deep learning became popular, the need for huge amounts of data has risen. The major problem faced in deep learning is the data scarcity. Many researchers have done research in areas such as image processing, pattern recognition, artificial intelligence, and cognitive science to solve handwritten character recognition problem but the data availability remains the problem particularly in Indian languages. The main motive of this paper is to generate the handwritten character of Devanagari, for which DCGANs are used which help us to generate training data images from the vector representation. Here, we use three-layer CNN having a stride value of two for feature extraction of the handwritten character. The characters generated look like the character in the original dataset.