Rice Grain Quality Grading using Digital Image Processing Techniques
Y. Supraja, P. Subbarao, K. Sri Tapaswi, P. Vemanth Harsha, Sri M. Dilip Kumar
Abstract
Grain quality is extremely important to humans since it has a direct impact on their health. As a result, there is a considerable requirement to test grain quality and identify adulteration or non-quality materials, and manually evaluating grain samples is a time-consuming and complicated operation. Errors are possible due to the subjectivity of human perception. Machine vision-based solutions have evolved to attain uniform standard quality and precision. Rice quality is determined by a mix of physical and chemical factors. Chalkiness, whiteness, milling degree, bulk density and, grain size and form are all factors to consider. Some physical qualities include moisture content. This paper compiled a list of all physical characteristics and graded the rice grains using canny edge detection.