Grain quality detection by using image processing for public distribution

In our life food is necessary for nourishment and sustenance. There are some additional impurities present in the food such as stones, damaged seeds, broken granules which affects the composition and the quality of food. Determining the quality of grains is a big challenge. Wheat and rice are used by most of the population across the world. In this paper, we have proposed a system that determines the quality of food. Initially, the grain samples run on the conveyor belt and then random images of grains are captured by the camera. The image processing algorithm is applied on the grain samples through MATLAB. The classification has been done according to colour, shape and size. It results good, bad and medium quality by using Neural Network (NN) classifier. The final output is displayed on the LCD also the message will be sent to higher authority through GSM module. This system can be implemented in food industries at later stage for grading purpose which will ma the task of classification of grains simpler for the public.