Plant Leaf Disease Detection Using Fuzzy C-Means Clustering Algorithm
A. Kumari,  S.Meenakshi,  S. Abinaya
India, the country where the main source of income is from agriculture. Farmers grow a variety of crops based on their requirement. Since the plants suffer from the 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 a 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 Fuzzy C-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 an accuracy of 92%.
Keywords- Image Processing, Leaf diseases detection, K-means clustering, feature extraction, Multiclass SVM Classification
Cite this Article
A. Kumari,  S.Meenakshi,  S. Abinaya,   "Plant Leaf Disease Detection Using Fuzzy C-Means Clustering Algorithm"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 3, pp.157-163, July 2018, Available at :http://www.ijedr.org/papers/IJEDR1803028.pdf