This paper holds a survey on various technique of disease detection through leaf images. Digital image processing is fast, reliable and accurate technique for detection of diseases, various algorithms are also used for identification and classification of leaf diseases in plant. This paper presents techniques employed by different author to identify disease like machine learning, deep learning, artificial neural network, image processing. the foremost focus of this paper is to go looking various technique to identify disease. Disease during a crop ends up in small efficiency and successively ends up in huge damage to the agronomists. Thus, recognition of disease in initial phase are going to be helpful for agronomist in order that essential actions will be taken. This paper discusses machine learning techniques to detect the disease within the plant with the assistance of the image of the plant. Accurate plant diagnosis requires experts’ knowledge but is typically expensive and time consuming. Therefore, it's become necessary to style an accurate, easy, and low-cost automated diagnostic system for plant diseases. This paper present survey on different classification techniques that may be used for plant disease classification. A classification may be a technique where leaf is classed supported its different morphological features. There is such a large amount of classification techniques like k-mean clustering, Support Vector Machine.