A Review paper On Fruit/Leaf/Plant Disease Detection Using various Image Processing Approaches
Keywords:
Leaf diseases, SVM, segmentation, morphological processing, features extraction, clustering, fuzzy logic, Back Propagation Neural Network, CCV, K-means Clustering, LBP, SVMAbstract
This paper holds a survey on leaf disease detection using various image processing technique. Digital image processing is fast, reliable and accurate technique for detection of diseases also various algorithms can be used for identification and classification of leaf diseases in plant. This paper presents techniques used by different author to identify disease such as clustering method, color base image analysis method, classifier and artificial neural network for classification of diseases. The main focus of our work is on the analysis of different leaf disease detection techniques and also provides an overview of different image processing techniques. This paper also discuss about Fruit disease cause a calamitous problem and results in economic and agricultural industry loss. Earlier detection of infected fruit had done manually but now with the advancement in technology image processing techniques was developed. There are two phases; first is for training and the other is for testing. In training phase, all the data related to the infected and non-infected fruit is stored and in testing phase, it is analyzed that whether the fruit is infected or not and if yes then by which disease. In this paper, the different existing techniques used to detect the infected fruit are discussed. These techniques are proved to be beneficial for the farmers as they help in detection of fruit disease in early stages.
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