A machine vision based smart conveyor system

Abstract

Material flow detection on conveyor based on machine vision is the research topic of this paper. A belt conveyor system equipped with a camera and micro-controller is used as the test apparatus. The purpose of this experiment is to obtain the quantity of material on the conveyor belt using machine vision and then develop an intelligent speed adjustment system for belt conveyor according to the quantity, so as to avoid waste of energy and reduce the wear of the conveyor. Three image processing algorithms that developed, applied and compared were: 1) Background Subtraction; 2) Canny edge detection and morphological operations; 3) Particle analysis using. It is observed that all three methods perform well for material detection on the conveyor belt. However, the particle analysis method resulted in higher reliability and accuracy with faster processing speed. The research provides new developmental ideas for intelligent conveyor systems.