The quality of grain is of great importance for human beings as it directly impacts human health. Hence there is a
great need to measure the quality of grain and identifying non-quality elements. Analysing the grain samples manually is a more
time-consuming and complicated process, and having more chances of errors with the subjectivity of human perception. To
achieve uniform standard quality and precision, machine vision-based techniques are evolved. Rice quality is nothing but a
combination of physical and chemical characteristics. So, to get the physical characteristics of the rice grains, image processing
techniques are applied. Grain size and shape are some physical characteristics. The obtained all physical features grades the rice
grains using canny edge detection.
