This paper is published in Volume-3, Issue-2, 2017
Area
Digital Image Processing
Author
Niveditha C. R, Megha .S, SowmyaShree .N, Vidhya .K
Org/Univ
East west institute of technology, Bengaluru, India
Pub. Date
27 March, 2017
Paper ID
V3I2-1268
Publisher
Keywords
FCM clustering, Automatic recognition, SVM, Plant leaves diseases, Symptom, Prevention, Image Segmentation.

Citationsacebook

IEEE
Niveditha C. R, Megha .S, SowmyaShree .N, Vidhya .K. Image Processing Technique for Plant Disease Identification Using FCM Clustering Technique, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Niveditha C. R, Megha .S, SowmyaShree .N, Vidhya .K (2017). Image Processing Technique for Plant Disease Identification Using FCM Clustering Technique. International Journal of Advance Research, Ideas and Innovations in Technology, 3(2) www.IJARIIT.com.

MLA
Niveditha C. R, Megha .S, SowmyaShree .N, Vidhya .K. "Image Processing Technique for Plant Disease Identification Using FCM Clustering Technique." International Journal of Advance Research, Ideas and Innovations in Technology 3.2 (2017). www.IJARIIT.com.

Abstract

Our paper focuses on providing information about plant diseases and prevention methods. Plants have become an important source of energy, and are a fundamental piece of the puzzle to solve the problem of global warming. There are many types of diseases which are present in plants. Diseases weaken trees and shrubs by interrupting chemical change, the method by that plants produce energy that sustains growth and defense systems and influences survival. This paper presents an improved method for plant disease detection using an adaptive approach. This approach helps to increase the accuracy of the disease level, it provides various prevention method (type and amount of pesticides to be used), the level of destruction and helps to check whether the disease spreads or not.