Devanagari Character Recognition Using Bi-Dimensional Empirical Mode Decomposition

The handwriting recognition is matured for Roman, Japanese and Chinese and Arabian language scripts but for Indian languages a lot of scope is there. For Indian languages most of the work is limited to isolated characters and numerals. This study is about the recognition of handwritten Devanagari characters. The character images are obtained from some research groups and bi-dimensional Empirical Mode decomposition is used for preprocessing the images. The deep learning based Convolutional neural network is used as the classifier. The Convolutional Neural Network (CNN) is based on connecting local region of the previous layer to the next layer. The obtained results are quite promising in terms of recognition error rate. Also the training time for this deep architecture of NN is quite less.