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图像处理技术在柠檬病害诊断中的应用 被引量:2

Identification of the Lemon Disease Based on Image Processing Technology
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摘要 文章深入探讨了图像增强,基于病斑颜色与外轮廓相结合的病斑分割,有效特征提取,以及分类器构建等相关技术。并以五种容易混淆的病害为例,提取其病斑的色调、纹理、形态三种特征向量,分别采用支持向量机和BP神经网络进行训练、测试。实验结果表明该方法能很好的识别柠檬病害类别,为科学防治和病害危害程度评价提供科学依据。 The paper proposed an identification method through the analysis of disease image,the effective feature is extracted anto maticall,and the classifier model is designed.In the paper method was studied how to enhancement processing the diseases of image,segmentat disease spot,extract feature,and Construct classifier model,etc.Then for example five of confusion between the diseases,extracting the disease spots the tone and texture,shape characteristics,after optimization respectively by using support vector machine(SVM) and BP neural network to identify disease categories.The experimental results show that this method can be a very good recognition plant disease categories for scientific control and give a scientific evaluation for the plant disease harm degree.
机构地区 德宏师专计科系
出处 《计算机与数字工程》 2012年第8期98-100,141,共4页 Computer & Digital Engineering
基金 国家社科基金项目(编号:09BMZ006)资助
关键词 图像处理 叶部病斑 支持向量机 模式识别 柠檬病害 image processing leaf lesion support vector machine pattern recognition lemon disease
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参考文献10

  • 1Sanyala P, PatelS C. Pattern recognition method to detect two diseases in rice plants[J]. The Imaging Science Journa, 2008, 56(6): 319-325.
  • 2王映龙,戴香粮.图像处理技术在水稻虫害系统中的应用[J].微计算机信息,2007,23(26):274-275. 被引量:13
  • 3蔡清,何东健.基于图像分析的蔬菜食叶害虫识别技术[J].计算机应用,2010,30(7):1870-1872. 被引量:17
  • 4[美]RafaelC.Gonzalez,RichardE.Woods,StevenLEd-dins.数字图像处理学[M].阮秋琦,译.北京电子工业出版社,2001.
  • 5Burgos-Artizzu X P, Riheiro A, TelIaeehe A, t'Nares G, Ferndndez-Quintanilla C. Improving weed pressure assessment using digital images from an experience-based reasoning ap- proach[J].Computers and Eleetronics in Agriculture, 2009, 65(2): 176-185.
  • 6管泽鑫,姚青,杨保军,胡洁,唐健.数字图像处理技术在农作物病虫草识别中的应用[J].中国农业科学,2009,42(7):2349-2358. 被引量:34
  • 7宁天夫.数字图像处理技术的应用与发展[J].舰船电子工程,2009,29(1):38-41. 被引量:24
  • 8边肇祺 张学工.模式识别[M].北京:清华大学出版社,2002..
  • 9Burges C J C. A totorial on support vector machines for pat tern recognition[J]. Data Mining and Knowledge Discovery, 1998, 2(2):121-169.
  • 10Steve R Gunn. Support vector machines for classification and regression[R]. Technical Report, Southampton: University of Southampton, 1998 : 1-28.

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