The research on the judgment of paddy rice's nitrogen deficiency based on image

Abstract

Because of the unreliability judgment of paddy rice's nitrogen deficiency depending on the traditional artificial naked eye, in this article, the way of the paddy rice's nitrogen deficiency examination based on image is put forward, to achieve the precise fast lossless detection and judgment on the paddy rice's nitrogen. Based on the sorting function of SMV, paddy rice leaf's visible images are gathered, the texture features of image are extracted, the RBF nuclear function is chosen, the penalty coefficient C and the regularity coefficientγ are set, and the SVM sorting model is constructed. The recurrence sentencing rate to the training sample achieves 100%. The examination is caught on the test sample, and the accuracy rate of examination recognition achieve 95%, which indicates that the method of paddy rice's nitrogen lossless examination judgment by image is effective and feasible to achieve the precise fast judgment on paddy rice's nitrogen. © 2009 Springer Science+Business Media, LLC.