Automatic Classification of Chinese Herbal Based on Deep Learning Method

Abstract

In today's society, people's living standards are getting better and better. At the same time, many problems have also appeared in the diet, which has led to an increase in the incidence of diseases. Chinese herbal medicine has been widely used in the treatment of many diseases. But it is a problem for the collection and classification of Chinese herbal medicines. There are a wide variety of Chinese herbal medicine plants, and there are also some Chinese herbal medicine plants that look very similar. Even a taxonomist can hardly distinguish every herbal medicine, let alone for beginners. So we designs a method to automatically identify and classify Chinese herbal medicines by processing images and deep learning method, which can greatly reduce the workload, and improve the efficiency of work. The technology of Chinese herbal medicine recognition and identification based on image processing and deep learning method can effectively overcome the shortcomings of manual recognition that require rich experience. At present, deep learning is more and more popular, especially for image classification, so we use GoogLeNet to classify 50 kinds of Chinese herbal medicine by their images under natural conditions with complex backgrounds. And the method achieved good performance. TOP-1 achieved an accuracy of 62.8%, and TOP-5 achieved an accuracy of 89.4%.