ADVANCED ENSEMBLE CLASSIFIER APPROACH FOR TOMATO PLANT DISEASE CLASSIFICATION
Padmaja Goli#1, S Venkateswarlu *2
#1,2 Computer Science and Engineering, KLEF, Vijayawada, India
#1Research Scholar, KLEF, Vijayawada
Professor, KLEF, Vijayawada, India
Abstract: Advances in various technologies which have been applied on various sectors implemented in Agriculture sector too. Application of latest technologies includes Major areas like Medicine, Space, Banking, Security Systems along with Agriculture which help to yield quality and quantity enhanced products. Agriculture application of technology helps in early disease detection, classification and prevention that help farmers to protect the crops and enhance quality of the food products being produced. Early detection of diseases that may occur in plants stands as a primary solution to prevent losses in the harvest and amount of agricultural products been grown. The important objective of the proposed work is to develop a method to identify plant diseases and classify the disease using advanced Ensemble classifier. The mixture of multiple features helps to identify and classify diseases in less time reducing Computational time and improve accuracy. The working methodology followed is Segmentation, Feature Extraction, Feature Selection and Classification. The performance of the proposed work has been measured by precision and accuracy.
Keywords: Ensemble Classifier, Image Segmentation, Feature Extraction, Image Preprocessing, Plant Disease, Segmentation.