Open AccessDETECTION OF PLANT LEAF DISEASES IN AGRICULTURE USING RECENT IMAGE PROCESSING TECHNIQUES – A REVIEW
Author(s) -
Arpan Singh Rajput,
Shailja Shukla,
Sanjeev Thakur
Publication year - 2019
Publication title -
international journal of students research in technology and management
Language(s) - English
Resource type - Journals
ISSN - 2321-2543
DOI - 10.18510/ijsrtm.2019.716
Subject(s) - agriculture , productivity , product (mathematics) , plant disease , population , image processing , agricultural engineering , agricultural economics , microbiology and biotechnology , computer science , geography , biology , engineering , mathematics , environmental health , image (mathematics) , artificial intelligence , medicine , economics , economic growth , geometry , archaeology
Purpose: Agricultural productivity is something on which the economy highly depends in India as well in all over the world. India is an agriculture-dependent country; wherein about 70% of the population depends on agriculture.
Methodology: This is one of the main reasons that disease detection in agriculture plays an important role, as having the disease in plant leaf is quite natural. If proper observations are not taken in the agriculture field then it causes serious effects on plants due to which respective product quality and productivity are affected. Detection of plant leaf disease through effective and accurate automatic technique is beneficial at the starting stage as it reduces a large work of monitoring in big farms of crops.
Result: This paper presents the review on the state of the art disease classification techniques presently used using image processing that can be used for plant leaf disease detection in agriculture.