Non-destructive quality assessment of Fruits is essential and exceptionally fundamental for the sustenance and rural industry. The Fruits in the market ought to fulfill the buyer inclinations. Generally reviewing of Orange fruit is performed basically by visual examination utilizing size as a specific quality characteristic. Picture preparing offers answer for computerized Orange Fruits estimate reviewing to give exact, solid, predictable and quantitative data separated from dealing with extensive volumes, which may not be accomplished by utilizing human graders. This Research shows an Orange size and Bacteria Spot Defect distinguishing and reviewing framework dependent on picture preparing. The early appraisal of Orange quality requires new apparatuses for size, color and texture estimation. Subsequent to catching the Orange side view picture, some fruits characters is removed by utilizing identifying calculations. As indicated by these characters, reviewing is figured it out. The benefit of high precision of evaluating, rapid and ease. It will have a decent prospect of use in OrangeFruit quality distinguishing and evaluating zones. In this paper we will elaborate different types of features and classification methods using advantages and disadvantages.

Image Processing, K-Means clustering, Color features, Texture features, Shape feature, Random forest classifier, SVM, ANN

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