In the wide range of crops grown in India, fruits play a prominent role as it helps in good revenue for the farmers. Among them, the grape is extensively grown, as regular plants grapes also have various diseases that infect their fruits, stem and leaf that in turn affect yield. In the proposed work, diseases that infect leaves are considered such as fungi, viruses and bacteria and others are subjected to an automated disease detection algorithm. Automated disease detection will improve the diagnosis accuracy actions can be controlled more appropriately at the correct time. A widely employed method in these scenarios is, Image processing which is endorsed for leaf disease identification in plants and also helps in classification. Here, it is proposed to compare the algorithms that are categorized under supervised learning such as KNN and SVM that are implemented on image feature extraction techniques such as HOG, LBP and GLCM.