Study On A Automatic Classification Method For The Tobacco Leaf Structure With Image Processing

Today, analyzing the tobacco leaf structure still depends on manpower in the tobaccoindustry. To overcome the flaw of the conventional method of detecting and classifying thetobacco leaf structure, the study and application of image processing in the tobacco leafstructure automatic classification is introduced. Discuss the selection principle of the keyhardware for the image acquisition, which are used in the tobacco classification system.And the transmission of digital image data is presented. Then the details of some mainimage processing algorithms such as image enhancing, color image segmentation,connected component labeling, area detecting, recognizing and classifying are analyzed.This paper presents a algorithm—the maximum ratio of variance, for classifying thetobacco leaf area dynamically. It based on the concept of the scatter of classification. Thealgorithm is adaptive to various quality tobacco images. The algorithm is precious and theprocessing time is decreased. It also runs in real time. Experimental results show that itworks efficiently and stably with the tobacco leaf structure classifying automaticallysystem. The practical results show that it is feasible and satisfactory.