耿长兴,张俊雄,曹峥勇,李伟.基于色度和纹理的黄瓜霜霉病识别与特征提取[J].农业机械学报,2011,42(3):170-174.
Geng Changxing,Zhang Junxiong,Cao Zhengyong,Li Wei.Recognition and Features Extraction of Cucumber Downy Mildew Based on Color and Texture[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(3):170-174.
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基于色度和纹理的黄瓜霜霉病识别与特征提取   [下载全文]
Recognition and Features Extraction of Cucumber Downy Mildew Based on Color and Texture   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  黄瓜霜霉病  温室  识别  特征提取  颜色  纹理
基金项目:国家高技术研究发展计划(863计划)资助项目(2008AA100905、2007AA04Z222)、高等学校博士学科点专项科研基金资助项目(200800191014)、中国农业大学科研启动基金资助项目(2007027) 和中国农业大学基本科研业务费研究生科研创新专项
作者单位
耿长兴 中国农业大学 
张俊雄 中国农业大学 
曹峥勇 中国农业大学 
李伟 中国农业大学 
中文摘要:研究了可见光波段的黄瓜霜霉病信息分布和分割方法,有效实现了温室非结构环境下黄瓜病害信息识别。通过研究温室黄瓜图像在RGB、HIS和YCbCr颜色空间的分布特点,建立了光照分析模型,提高了不同光照条件下的病害提取适应性。分析了病害目标与环境背景Cb和Cr均值差,提出了CbCr组合算法,实现了目标的快速有效识别,满足了实时对靶施药的要求。通过随机抽取30幅黄瓜霜霉病图像进行算法验证,结果表明图像的平均识别正确率达90.6%。
Geng Changxing  Zhang Junxiong  Cao Zhengyong  Li Wei
China Agricultural University;China Agricultural University;China Agricultural University;China Agricultural University
Key Words:Cucumber downy mildew, Greenhouse, Recognition, Features extraction, Color, Texture
Abstract:An extraction algorithm based on color and texture was developed to realize segmentation between downy mildew and cucumber plants in greenhouse. A light analysis model was established by comparing the distribution of cucumber images in RGB, HIS and YCbCr color space, which was beneficial to the recognition of disease in variable illuminations. Combination model of Cband Cr elements was built based on the mean difference of lesions and interference informations in Cb and Cr, which included leaves, poles and soil, and extracted target rapidly. A detecting expriment was carried out on 30 images with downy mildew, which were taken in a changing greenhouse enviornment. The results indicated that the accuracy rate of segmentation was 90.6%. 

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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