Quality Testing of Rice grains using Neural Network


The quality of the food product we have a tendency to consume is of additional importance, as individuals are getting educated their demand for quality of grains is increasing. there’s risk of adulteration of food grains by the traders. usually, the standard assessment is carried by the visual review that is a manual method.

during this work a picture process technique is employed as an endeavor to change {the method|the technique} that overcomes the drawbacks of manual process Associate in Nursing automatic analysis method for the determination of the standard of rice granules and grain kind identification is introduced victimization Neural Network.

A model of quality testing and identification is constructed that is predicated on geometric options and color options with the technology of laptop image process and neural network. These options square measure conferred to the neural network for coaching functions. The trained network is then accustomed determine the unknown grain varieties and its quality. The grading of rice sample is finished in step with the dimensions of the grain kernel. This technique offers smart leads to an analysis of rice quality

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