Research On Tobacco Grading Based On Outline Feature

The grading of flue-cured tobacco leaf is still accomplished by manpower at present. Experts are trained to classify the flue-cured tobacco leaf by hand according to their sense and experience.To overcome the flaw of the conventional method of classifying the flue-cured tobacco lear,the study of image processing and pattern identification in the flue-cured tobacco leaf automatic classification is carded out and a contour-based automatic grading technique is introduced.A grading model is established by Bayes analysis through the coefficients of fitting polynomial and length-width ratio after the edge extracting and fitting,then flue-cured tobacco leave's growing position can be automatically classified at last.This paper introduced the framework of image collecting system and techniques in image reading and displaying.On the basis of analyzing many pretreatment algorithm for flue-cured tobacco leaf,such as image smoothing,segmentation,binarization and rotation, the improved fast median filter was applied to denoising,while the relative variation coefficient method combined with the small area removing method was used in image segmentation.After a comparison among many edge detecting and fitting methods,the two element orthogonal polynomials showed advantages,so it was adopted as the main edge fitting method.And a character database was structured for the coefficients of the two element orthogonal polynomials and also for the length-width ratio of flue-cured tobacco leaves.Lastly,the classification model was established for flue-cured tobacco growing position by using the Bayes discriminant analysis,a least wrong classifying rate method.Experimental results showed that it worked efficiently with the tobacco automatic grading system by using the Bayes discriminant analysis.The practical results also showed that it could be extended into the application of variety identification for flue-cured tobacco leaf.