王守志,何东健,李文,王艳春.基于核K—均值聚类算法的植物叶部病害识[J].农业机械学报,2009,40(3):152-155.
.Leaf Disease Recognition Based on Kernel K-means Clustering Algorithm[J].Transactions of the Chinese Society for Agricultural Machinery,2009,40(3):152-155.
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基于核K—均值聚类算法的植物叶部病害识   [下载全文]
Leaf Disease Recognition Based on Kernel K-means Clustering Algorithm   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  植物病害  病害识别  核K—均值聚类
基金项目:
王守志  何东健  李文  王艳春
西北农林科技大学
中文摘要:针对植物叶部病害图像的特点,首先对采集到的玉米病害彩色图像采用矢量中值滤波法去除噪声,然后提取玉米病叶彩色图像的纹理特征和颜色特征作为特征向量,利用Mercer核,把输入空间的样本映射到高维特征空间进行K—均值聚类以及植物病害识别。试验涉及的4种玉米病害识别正确率达82.5%,核K—均值聚类方法适合玉米叶部病害分类。
Key Words:
Abstract:Based on the features of plant disease image, vector median filter was firstly applied to remove noise of the acquired color images of grape leaf with disease. Then texture features and color features of color image of leaf with disease were extracted as feature vector. And by using Mercer kernel functions, the data in the original space was maped to a high-dimensional feature space in which the data has been clustered efficiently. The precision of four kinds of experimental maize diseases recognition is 82.5%, and kernel K-means clustering algorithm suited the plant leaf disease classification recognition.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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