Indian Economy mainly determined by the agriculture. Tomato is one of the highest used food crops in India. Due to which detection of disease on tomato plant becomes essential. The manual detection of plant diseases are very complex and high cost. Hence, image processing based detection of plant diseases gives the solution. Disease detection involves the steps like image capturing , various processing steps and classification. Most of the diseases of tomato plant detected at initial stages as they affect leaves first. By detecting the diseases at initial stage on leaves will surely avoid impending loss. The classifier, the classification is performed to classify the healthy and disease affected tomato leaves. Finally, the performance of K-nearest neighbor (KNN) and multi class Support Vector machine (SVM) are compared. The proposed system assured an excellent performance to farmers and researchers in admissible way.

Diabetic Retinopathy is an eye disease which is caused by excessive sugar level in blood. Insufficient secretion of insulin hormone is the ground for evolution of diabetes. It affects most of the important organs in our body. There are two types of DR: Non Proliferative Diabetic Retinopathy and Proliferative Diabetic Retinopathy. In this proposed system techniques are introduced to detect and classify neovascularisation. Input fundus image is preprocessed by median filtering and further new vessels are segmented by using Fuzzy c-means clustering algorithm. After segmentation SIFT features are extracted and are used to train support vector machine (SVM) classifier. This automated system has been tested for 70 fundus images and accuracy of 96% is achieved