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半监督模糊聚类及其在羊蹄甲叶片识别的应用
引用本文:程碧霞,杨美玲,林碧蕊,杨昔阳.半监督模糊聚类及其在羊蹄甲叶片识别的应用[J].泉州师范学院学报,2013,31(2):25-28.
作者姓名:程碧霞  杨美玲  林碧蕊  杨昔阳
作者单位:泉州师范学院数学与计算机科学学院,福建泉州,362000
基金项目:福建省教育厅科技项目,泉州科技项目,福建省"大学生创新创业训练计划"项目
摘    要:提出了一种半监督模糊聚类算法,给出了它的迭代公式,指出该算法可以有效提高聚类算法的效率.结合Fisher降维方法,从叶片的色调、绿色灰度的18个特征中提取出两个主分量,并采用这些二维数据对羊蹄甲角斑病的受害程度作聚类分析.结果显示,对40张使用了其类别属性参与聚类的叶片,聚类结果与这些属性的一致率达100%,而对于其他数据,一致率也达到95%以上.

关 键 词:羊蹄甲角斑病  主成分分析  半监督模糊聚类

A Semi-supervised Fuzzy Clustering Method and Its Applications in the Bauhinia Blades Recognition
CHENG Bi-xia , YANG Mei-ling , LIN Bi-rui , YANG Xi-yang.A Semi-supervised Fuzzy Clustering Method and Its Applications in the Bauhinia Blades Recognition[J].Journal of Quanzhou Normal College,2013,31(2):25-28.
Authors:CHENG Bi-xia  YANG Mei-ling  LIN Bi-rui  YANG Xi-yang
Institution:( School of Math and Computer Science, Quanzhou Normal University, Fujian 362000, China)
Abstract:A semi-supervised fuzzy clustering algorithm is proposed,and its iterative formula is given. This new algorithm can effectively improve the efficiency of the clustering algorithm.Combined with Fisher algorithm,two principal components are extracted from the 18 hue statistics and green values, This semi-supervised clustering analysis is applied to recognize the angular leaf spot victims of Bauhinia.The results showed that the consistent rate is 100% for the labeled leaves,and above 95% for other leaves.
Keywords:Bauhinia angular leaf spot  principal component analysis  semi-supervised fuzzy clustering
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