Analysis and Recognition of Rice Granules using Image Processing and Neural Network

in foodstuff trade, grading of food resources is essential because samples of foodstuffs are subjected to adulteration. In the earlier, granules were categorized through sieves or other mechanical way for grading purposes. Investigation is made on basmati rice by image processing and Neural Network which is implemented based on the features extracted from rice granule. Digital imaging is acknowledged as a proficient system, to haul out the features from rice granules in a non-contact mode. Images are acquired for rice using Webcam. Image Pre-processing techniques, Ostu's Thresholding, Canny edge detection, Feature extraction are performed on the acquired image using image processing method through MATLAB. The morphological features extracted from the acquired image are given to Neural Network Pattern Recognition Tool. By using the vibration technique segregation of graded rice is done. This effort has been taken to categorize the appropriate quality of specified rice sample based on its parameters. The performance of image processing reduces the time of action and enhanced the crop identification significantly.