Deep learning for handwritten Javanese character recognition

Abstract

Javanese character is traditional character from Indonesia. The character is used to write most of literature works from Kingdom era in Indonesia, for example Majapahit Kingdom and Mataram Kingdom. However, due to its rarely use in daily activities, most Javanese are now unable to recognize Javanese characters. The importance of Javanese characters in Indonesia's culture motivates some researchers to perform study on this topic. Several researches have been performed to classify Javanese characters with various method, however the accuracy are still low. On the other hand, deep learning has performed well in image classification. In this paper, the use of deep learning technique to classify handwritten Javanese characters is studied. The classification used 2470 images from 20 javanese characters. The size of input image used is 32×32 pixel. The classification is performed by using convolutional neural network (CNN) and Deep Neural Network (DNN). The accuracy with k-fold cross validation obtained are 70.22% and 64.65% for CNN and DNN, respectively.