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Abstract
Recently, a lot of activity in the area of Image Categorization has been done. In respect of produce fruit and vegetable classification problem, Veggie-vision [2] was the first attempt of a fruit and vegetable recognition system. The system uses texture, color and density (thus requiring some extra information from the system). This system does not take some advantage of recent developments, because it was created some time ago. The reported accuracy was around 95% in some scenarios but it uses the top four responses to achieve such result. Our data set is more demanding in some respects; while the data set of Veggie-vision had some extra classes, the hardware that captures the images gave a suppressed specular lights and more uniform color. The data set gathered in the super market has more illumination differences and much color variation among different images, and there is no measure for the suppression of specularities. Diseases in fruit cause devastating problem in production and economy in agricultural industry worldwide. Till now experts identify the presence of the disease in the fruits manually, but it is expensive for a former to consult an expert due to their distant availability, so it is required to detect the symptoms of the fruit diseases automatically as early as they appear on the growing fruits. Apple fruit diseases can cause major losses in yield and quality appeared in harvesting. To know what control factors to take next year to avoid losses, it is crucial to recognize what is being observed. Some disease also infects other areas of the tree causing diseases of twigs, leaves, and branches. Some common diseases of apple fruits are apple scab, apple rot, and apple blotch [52]. Apple scabs are gray or brown corky spots. Apple rot infections produce slightly sunken, circular brown or black spots that may be covered by a red halo. Apple blotch is a fungal disease and appears on the surface of the fruit as dark, irregular or lobed edges.