Review on Detection and Classification of Vegetable Diseases
Published: 2015
Author(s) Name: Mamta Yadav, Toran Verma |
Author(s) Affiliation: Department of CSE, Rungta College of Engg. & Technology, Bhilai, Chhattisgarh, India.
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Abstract
Diseases in vegetable can cause significant economic, social & ecological loss globally. The disease can affect any part of the crop. For analysis of different types of diseases image processing has been proved to be an effective tool in various fields. Usually, for manual inspection the features of the diseases are extracted. But by machine inspection diseases can be identified automatically and it can be great profit to those users who have not having knowledge about the crop that they are cultivated. There are many classification techniques such as K-mean clustering, fuzzy c-mean clustering, Genetic Algorithm(GA), Back Propagation Neural Network (BPNN), Support Vector Machine(SVM) and Principal Component Analysis (PCA) etc. The aim of this research work is to present an overview of different methods and techniques which was followed in some important research work in the field of image processing for vegetable diseases and gives the general approach to use these techniques.
Keywords: Back Propagation, Neural Network, Principal Component Analysis Image Processing Genetic Algorithm K-mean Clustering Vegetable Diseases
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