Rice Quality Analysis Using Image Processing Techniques

The quality of food grains is becoming increasingly important as individuals become more educated and demand better quality food grains. There is always a chance of food grain adulteration by traders. Usually, the quality ajssessment is done by visual inspection, which is a manual method. In this study, we propose an image processing technique as an effort to objectively address the shortcomings of having a manual process. This paper reports the banana quality assessment of rice grains based on their size. The grains were categorized as grade 1, grade 2, and grade 3 according to size. We used different rice grain varieties, such as Basmati rice, Sona masuri, boiled rice, and egg rice, for testing. The system was developed based on an image data set, and the images were assigned to labels using a decision tree-based classification method. The outcomes have given us promising results.