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THE RESEARCH ON THE JUDGMENT OF PADDY RICE'S NITROGEN DEFICIENCY BASED ON IMAGE

机译:基于图像的水稻氮缺陷判断研究

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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 coefficient γ 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.
机译:由于水稻氮缺乏的不可靠性判断,根据传统的人工肉眼,在本文中,提出了基于图像的水稻氮缺陷检查的方式,实现了稻谷的精确快速无损检测和判断米的氮。基于SMV的分类功能,收集水稻叶片的可见图像,提取图像的纹理特征,选择了RBF核功能,设置了惩罚系数C和规则性系数γ,构建了SVM分选模型。 。训练样本的复发判决率达到100%。考试捕获了测试样品,检查识别的准确率达到95%,这表明水稻氮气无损检测的方法是有效的,可行的,以实现对水稻氮的精确判断。

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