Quantity Intelligent Reckoning for Packaged Granary Grain Based Onimage Processing

This paper presents a quantity intelligent reckoning approach for packaged granary grain based on image processing. The actual scene video was taken as the analysis object, and the dual-threshold Canny operator and the morphology processing method are used to extract the object grain bags’ characteristic outline-the boundary of the counter-band of light. Then, a counting algorithm which integrates mode theory and variance analysis technology is presented for the quantity second-judgment. Experimental results show that by accurately extracting the characteristic outline and counting the number of the characteristic outline, the algorithm presents an effective method for grain quantity detection with high recognition precision and efficiency.