Leaf Detection

Leaf Detection

Mr. Pushkar R. Bagane1, Mr. Nikhil S. Chavan2,

Mr. Harshvardhan V. Patil3,

Mr. Nikhil K. Patil4, Mrs. P. S. Bodake 5

Computer Engineering Department, Sharad Institute of Technology Polytechnic, Yadrav , India

Abstract:

Agriculture is the backbone of Indian government. Every human being has a requirement of a lot of production of crops to fulfill the needs of Indian government. Because of some diseases that we observe in this day-to-day life, a large amount of crop production is being decreased. There are various types of diseases on plant leaves and as well as for the crop, that causes problems in development of crops. Human eyes don't have the capacity to identify so strongly with our naked eye. It is too difficult to identify the plant diseases on leaves. The automatic disease detection system is used to automatically detect and identify the diseased part of the leaf images and it classifies plant leaf disease using image processing techniques. By gathering some of the leaves and training those leaves. We use this training data to train our data and then output will be predicted with optimum accuracy. For this we use the Django framework. We upload the image into the website we have developed. Now the patterns of the uploaded image are compared with patterns available in the dataset, which is almost accurate, resulting in identification of the plant disease. At the starting stage, the disease can be easily identified. Proposed model helps to reduce efforts or hard work of farmers for monitoring big farms and related diseases to farms and crops.

Keywords:

VGG16, VGG19, Django, Image Processing, Data Augmentation, Tensorflow, Keras.