Matching and Grading of Variety of Rice Grains

In the present work a digital imaging approach has been devised in order to investigate different types of characteristics to identify the rice varieties. Two different common rice varieties were used in tests for defining. These include existing standards for rice Area Aspect ratio rmean gmean bmean entropy_r entropy_g and entropy_b. It successfully shows the effectiveness of compactness as its features. The database of the present work recognizes the rice which has been trained and identified. With proper selection of software tools a low cost tool is designed for quality analysis of rice grains which provides all relevant parameters about rice grains by image analysis. Hence it aims for accurate classification of micro calcification of different types of rice varieties used in testing and producing accurate result.