This paper is published in Volume-3, Issue-4, 2017
Area
Image Processing
Author
Pooja Kulinavar, Vidya I. Hadimani
Org/Univ
KLE Society's Dr. M. S. Sheshgiri College of Engineering and Technology, Belagavi, Karnataka, India
Keywords
Image Processing, Leaf Diseases Detection, K-means Clustering, Feature Extraction, Multiclass SVM Classification
Citations
IEEE
Pooja Kulinavar, Vidya I. Hadimani. Classification of Leaf Disease Based On Multiclass SVM Classifier, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Pooja Kulinavar, Vidya I. Hadimani (2017). Classification of Leaf Disease Based On Multiclass SVM Classifier. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.
MLA
Pooja Kulinavar, Vidya I. Hadimani. "Classification of Leaf Disease Based On Multiclass SVM Classifier." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.
Pooja Kulinavar, Vidya I. Hadimani. Classification of Leaf Disease Based On Multiclass SVM Classifier, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Pooja Kulinavar, Vidya I. Hadimani (2017). Classification of Leaf Disease Based On Multiclass SVM Classifier. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.
MLA
Pooja Kulinavar, Vidya I. Hadimani. "Classification of Leaf Disease Based On Multiclass SVM Classifier." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.
Abstract
India, the country where the main source of income is from agriculture. Farmers grow variety of crops based on their requirement. Since the plants suffer from disease, the production of crop decreases due to infections caused by several types of diseases on its leaf, fruit and stem. Leaf diseases are mainly caused by bacteria, fungi, virus etc. Diseases are often difficult to control. Diagnosis of the disease should be done accurately and proper actions should be taken at the appropriate time. Image Processing is the trending technique in detection and classification of plant leaf disease. This work describes how to automatically detect leaf diseases. The given system will provide fast, spontaneous, precise and very economical method in detecting and classifying leaf diseases. This paper is envisioned to assist in the detecting and classifying leaf diseases using Multiclass SVM classification technique. First the affected region is discovered using segmentation by K-means clustering, then features (color and texture) are extracted. Lastly, classification technique is applied in detecting the type of leaf disease. The proposed system effectively detects and also classify the disease with accuracy of 92%.