Quality Identification and Grading of Wheat Grains using Image Processing Techniques

Food is the basic need which provides nutrients to our body. Quality of food is the most necessary thing to be checked as the adulteration of food grains is increasing on a greater pace. Existing quality assessment is done manually which is tedious and include human errors (unknowingly or intentionally). This will affect the farmer who is relying on the farm for his daily bread, they don't get fair price after their years together efforts in farm. Manual Assessment is also encouraging adulteration of food grains thus deceiving the customers by mixing bad quality grains or materials which resemble the grains and gaining high margin profit. Automation is utmost necessary when human inspection is misleading the society and selling cheap quality food. This project illustrates the automatic grading system which process the grain image digitally and classify the grains into Good, Average and Bad class by taking predefined values into consideration with the help of Digital Image Processing and the grains, weed particles, stones and other foreign materials are easily distinguished. This can be achieved by training the system with a set of images and using these results, the system will test the input image. It can automate the process which is reliable, factual and time saving.