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.
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Dr. Rajlakshmi Ghatkamble schloss 2012 ihr Bachelor-Studium und 2014 ihr Master-Studium in Informatik und Ingenieurwissenschaften an der Visvesvaraya Technological University in Indien ab. Ihr Master-Praktikum schloss sie 2014 an der Changwon National University in Südkorea ab. Derzeit arbeitet sie am New Horizon College of Engineering.
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