Detection of Bacterial Blight on Pomegranate Leaf

In india, agricultural field plays vital role in the development of India. Smart farming is about empowering today’s farmers with the decision tools and automation technologies that seamlessly integrate products, knowledge and services for better productivity, quality and profit. In this paper, a solution for the detection of pomegranate leaf disease and also the solution for that disease after detection are proposed. The proposed system mainly consist image preprocessing, feature extraction, clustering and classification. The first steps consists image preprocessing in which images are resized. In second step, feature extraction is carried out. Color, morphology and color coherence vector features are used for the purpose of feature extraction . K-means clustering technique is used for partitioning training dataset into desired number of clusters according the features that has been extracted from the fruit images. Then the next step includes training and classification. Support Vector Machine approach is used for classification. DOI: 10.17762/ijritcc2321-8169.15064