
Digital Photogrammetry for Fruit Disease Identification
Author(s) -
G. Saranya,
B. Vidhya,
V Dhivya Dharshini,
M. Bharathi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/994/1/012009
Subject(s) - identification (biology) , agriculture , photogrammetry , disease , plant disease , field (mathematics) , agricultural engineering , computer science , business , geography , microbiology and biotechnology , engineering , artificial intelligence , medicine , mathematics , biology , pathology , ecology , archaeology , pure mathematics
Nowadays horticulture takes about 25% of the agriculture enterprise that has a excellent impact in the fruits field. Effective growth of crops and improved field culture must be incorporated to insure honest yield. To achieve that farmers need an environment friendly monitoring system. Farmers find it difficult to discover fruit ailment and its cause. Also, fruits are more prone to get infection in the course of cultivation, due to changing environmental condition and climate. The previous method concerning detecting fruit ailment was once more time ingesting and failed to supply information regarding the type of disease. Using the proposed fruit ailment discovery system, the agriculturist can determine the kind of the disease, and find preventive measures or suggestions. Image processing techniques are used for the enhancement of the received images. Then, convolution neural network has been used to make the model learn and classify the fruits and its disease. This system will benefit farmers across India.