Published Paper Details:

All over the world rice is the most consumed food and the requirement and demand of rice in the market is always high. In the market rice demand is always centered at the quality of rice depending upon its factors like length ,thickness of rice grain . Traditional methods to check all aspects of rice can be a very time consuming process and have to be done manually. Quality and purity checking of rice grains are commonly derived from human vision observation. Analyzing the rice grain sample manually is a longer consuming and sophisticated process, and having more chances of errors with the subjectivity of human perception. This paved the way for development of a computerized model for checking rice quality and all its aspects needed for checking the quality of rice. The strategies of digital image processing are used in this paper to provide a solution to the problem. Ninety percent).In proposed system model is built by clubbing both image processing and machine learning techniques to grade the rice .Digital Imaging is recognized as an efficient technique to extract the features from rice grains.We are also attempting to develop a Neural Network model in order to achieve better results.