Image processing are the important source of data and information in all fields, many types of Fruit and vegetable can be found in supermarket. When a cashier cannot scan the barcode, cannot recognize the fruit and vegetable that a customer wants. Software is needed to ease the process of vegetable recognition. The purpose of this paper is to simulate and design software that can be used to recognize different types of fruit and vegetable based on its shape and classification using neural networks. The system begins by collecting different types of both. Images are capture in fixed amount of light, background and other effects using a mobile camera (13 mega pixels) ,convert input image Gray; After the conversion process calculate the different intensity value, where the density value different of the object from the background so we determine the value of the threshold of separation between them. With the help of the threshold value convert gray image to binary image and used edges detect to determine the shape. Followed by training Neural Networks (NN) To recognition and classification For items, the accuracy system is 95 percent. Done using MATLAB 2017Ra software.
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