A multi-awarded agricultural engineer at the Bureau of Postharvest Research and Extension (BPRE) has developed a state-of-the art but low-cost computer vision system (CVS) for analyzing the quality of milled rice.
He is Dr. Manolito C. Bulaong. In his CVS, an ordinary scanner serves as the “eye” of the system. It replaces the expensive digital cameras used in the conventional CVS for image acquisition. The image processing software, on one hand, extracts the shape and color patterns from each grain image.
The artificial neutral network (ANN) meanwhile acts as the “brain” of the system. It recognizes the shape and color patterns from each grain and learns the quality category it belongs.