Published Paper Details:

This paper presents an automatic evaluation method for the determination of the qualityof rice granules.The quality of rice samples is to be determined with the help of color, and geometric features.A model of quality grade testing and identification is built which is based on appearance features such as area, major axis length, minor axis length, aspect ratio, the morphological and color with technology of computer image processing and neural network. The color and morphological features are presented to the neural network for training purposes. The trained network is then used to identify the unknown grain types and its quality.This proposed method gives good results in evaluation of rice quality.Chalky is whiteness part in the rice grain and it is one of the most important parameter that is used to evaluate the quality of rice grain. We proposed an image processing technique using extended maxima operator to detect the chalky area in the rice.We also calculated the dimensions and color to classify rice.