A survey on recognition and classification of paddy leaf diseases using image processing and machine learning techniques

From the past few years spreading of the pests and diseases in plants have been increasing significantly. Paddy plants
are the most important crop used in our country for the food, so it is most necessary to detect any disease of them within a short period of time for ensuring a proper and healthy growth of paddy plants. The process of manual disease detection requires labor and a large amount of time. Then utilizing the leaf images of plants for recognizing and classifying of diseases is the more focused research topic in the agriculture field. A survey on recognition and classification of paddy leaf diseases using image
processing and machine learning techniques is presented in this paper based on the disease infected leaf images of paddy plants. Firstly the concept of various plant diseases and the standard process of plant disease detection are discussed in this paper. A study and survey on the totally 5 papers of work is carried out in detail by covering a work on leaf diseases of the paddy plants based on the certain criteria. Such criteria are different preprocessing techniques, various diseases/ classes, different segmentation methods, various classifiers and accuracy of employed techniques. The experimental results of these various techniques are compared and evaluated to design a best on detecting and classifying of paddy plant leaf diseases.