Disease Detection and Diagnosis on Plant using Image Processing – A Review
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10.5120/18973-0445 |
Khushal Khairnar and Rahul Dagade. Article: Disease Detection and Diagnosis on Plant using Image Processing - A Review. International Journal of Computer Applications 108(13):36-38, December 2014. Full text available. BibTeX
@article{key:article,
author = {Khushal Khairnar and Rahul Dagade},
title = {Article: Disease Detection and Diagnosis on Plant using Image Processing - A Review},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {108},
number = {13},
pages = {36-38},
month = {December},
note = {Full text available}
}
Abstract
Diseases decrease the productivity of plant. Which restrict the growth of plant and quality and quantity of plant also reduces. Image processing is best way for detecting and diagnosis the diseases. In which initially the infected region is found then different features are extracted such as color, texture and shape. Finally classification technique is used for detecting the diseases. There are different feature extraction techniques for extracting the color, texture and edge features such as color space, color histogram, grey level co-occurrence matrix (CCM), Gabor filter, Canny and Sobel edge detector. There are also different classification techniques such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Backpropagation (BP) Network, Probabilistic Neural Network (PNN), Radial Basis Function (RBF) Neural Network.
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