A REVIEW ON IDENTIFICATION OF RICE GRAIN QUALITY USING MATLAB AND NEURAL NETWORK - MANSI KULKARNI; PROF. P. M. SONI (International Journal of Innovations in Engineering Research and Technology, 2021)
Quality of rice ismainlydefined from its chemical & physical characteristics. Quality of rice grainssampleis required for protecting the consumers from standardproducts because the samples of food materials are subjected to adulteration. In the present grain classificationsystem, grain category andquality are rapidly assessed by visual inspection. This processishowever, annoying and time consuming. The decision making capabilities of a grain inspector can be seriously affected by her/his physical condition such as eyesight and fatigue,mental state caused by biases and work pressure, and working conditions such as improper lighting, climate, etc. In This systemweused Image processingand using this technique we can classify the rice grainsample with accuracy. Themorphological features such as (area, perimeter, and length) extracted from the image and are given to Neural Network. This efforthas been prepared to classifythe appropriate quality of rice grain samplebased on its parameters