Bacteria Classification using Image Processing and Deep Convolutional Neural Network

Bacteria is one of the reasons that cause many diseases, and the diagnosis is hard to be done because of its shape and complexity. Thus, regularly the examination needs to be done by experts or specialists to classify the species of them and it also takes long time with the possibility on incorrect recognition. In Thailand there is still not enough experts to deal with it so the aim of this paper is to bring the new approach to classify the species of bacteria from Digital Image of Bacterial Species (DIBaS) by using Image Processing and Deep Convolutional Neural Network (DCNN) model to reduce the time consumption and increase the classification accuracy in traditional way. The result of the model gave the average accuracy at 95.09%.