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DETECTION OF UNHEALTHY PLANT LEAVES USING IMAGE PROCESSING AND GENETIC ALGORITHM WITH ARDUINO


Class Agnostic Image Common Ob
Abstract


India is an agricultural country and about seventy percent of our population depends on agriculture. One-third of our national income comes from agriculture. So the disease detection of plants plays an important role in the agricultural field. Majority of the plant diseases are caused by the attack of bacteria, fungi, virus etc. If proper care is not taken in this area, it may lead to serious effects on plants and adversely affects the productivity and quality. To detect, the plant diseases we need a fast automatic way. The main approach adopted in practice for detection and identification of plant diseases is naked eye observation through experts. The decision making capability of an expert also depends on his/her physical condition, such as fatigue and eye sight, work pressure, climate etc. So this method is time consuming and less efficient. Here, a project is proposed with an idea of detecting plant diseases using image processing. Image processing toolbox of Matlab is used for measuring affected area of disease and to determine the difference in the color of the disease affected area. This concept can be extended to detect the symptoms of any type of plant diseases that is affected on different horticulture crops. The algorithm can be used to classify the leaves and the classified outcomes are separated using Arduino based conveyor belt system. This reduces an important task of monitoring of farms crops at very early stage itself to detect the symptom of diseases appear on plant leaves.

KeyWords
Image processing Genetic algorithm Matlab Arduino Conveyor belt



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