Quality of rice is mainly defined from its chemical & physical characteristics. Quality of rice grains sample is required for protecting the consumers from standard products because the samples of food materials are subjected to adulteration. In the present grain classification system,grain category and quality are rapidly assessed by visual inspect ion. This process is however,annoying and time consuming. The decision making capabilities of a grain inspector can be seriously affected by her/his physical condition such as eyesight and fatigue,mental state caused by biases and work pressure,and working conditions such as improper lighting,climate,etc. In This system we used Image processing and using this technique we can classify the rice grain sample with accuracy. The morphological features such as (area,perimeter,and length) extracted from the image and are given to Neural Network. This effort has been prepared to classify the appr opriate quality of rice grain sample based on its parameters. https://www.ijiert.org/paper-details?paper_id=140987