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Image Processing for Grain Quality Monitoring

G.SRI LATHA 1 M.VENKATA NAGA LAKSHMI 2 K.SANDESH3 G.MADANMOHAN4M.MOUNIKA5 M.MOHANATEJAVENKATAMANIKANTA6

Asst. Professor, Sir C R Reddy College of Engineering[1]
UG Scholars, Sir C R Reddy College of Engineering[2,3,4,5,6]

ABSTRACT:
Food is an essential element for supporting life and providing nourishment. Nevertheless, contaminants like stones, damaged seeds, and broken granules are frequently found in food and   can have a negative impact on the content and quality of the food. Wheat and rice are two staples consumed by a majority of the world's population, making it important to ensure their quality. A system that can assess food quality has been offered as a solution to this problem. The classification of the grains is then determined by their color, shape, chalkiness and size, using a Probabilistic Neural Network (PNN) classifier to categorise them as good, bad, or medium quality.

KEYWORDS: Image Processing, Grain Quality, Neural Network.