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Machine Learning for Plant Disease Identification Tracking a | 102714

Zeitschrift für Biologie und heutige Welt

ISSN - 2322-3308

Abstrakt

Machine Learning for Plant Disease Identification Tracking and Forecasting for Farmers

Gandatti Sridhar*, H Parathasarathi Patra

Early pest detection is a major challenge in agriculture field. The easiest way, to control the pest infection is the use of pesticides. But the excessive use of pesticides are harmful to plants, animals as well as human beings. Integrated pest management combines biological and physical methods to prevent pest infection. The techniques of machine vision and digital image Processing are extensively applied to agricultural science and it have great perspective especially in the plant protection field, which ultimately leads to crops management. This paper deals with a new type of early detection of pests system. Images of the leaves affected by pests are acquired by using a digital camera. The leaves with pest images are processed for getting a gray colored image and then using feature extraction, image classification techniques to detect pests on leaves. The images are acquired by using a digital camera. The images are then transferred to a PC and represented in python software. The RGB image is then converted into gray scale image and the feature extraction techniques are applied on that image. The Support Vector Machine classifier is used to classify the pest types.

Haftungsausschluss: Diese Zusammenfassung wurde mithilfe von Tools der künstlichen Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert.