计算机工程与应用Issue(7)：154-157,4.DOI:10.3778/j.issn.1002-8331.1308-0316
小麦叶部常见病害特征提取及识别技术研究
Research on feature extraction and recognition of common diseases of wheat leaf
摘要
Abstract
This paper selects four common diseases of wheat leaf images, using image processing techniques to identify different types of disease. Firstly, the RGB color space is converted to HSV color space, the relevant color characteristics (hue and saturation)are extracted, and then geometry features(perimeter area, squareness, roundness, eccentricity, etc.) are extracted. To obtain the eigenvalues of each disease range, the sample images are analyzed, and then the eigenvalues of the unknown samples are used to identify different kinds of wheat diseases. This research takes powdery mildew and rust (leaf rust, stripe rust and stem rust)as research objects. Based on color characteristics, the powdery mildew and rust are identified, according to the shape characteristics, leaf rust, stripe rust and stem rust are identified. The proposed method is simple and convenient with an identification rate of more than 96%. The experimental results show that the chosen color and shape features of these four common diseases are valid and feasible for wheat diseases identification.关键词
小麦病害/特征提取/图像识别Key words
wheat disease/feature extraction/image recognition分类
信息技术与安全科学引用本文复制引用
王美丽,牛晓静,张宏鸣,赵建邦,何东健..小麦叶部常见病害特征提取及识别技术研究[J].计算机工程与应用,2014,(7):154-157,4.基金项目
国家高技术研究发展计划（863）（No.2013AA10230402）；中央高校基本科研业务费（No.ZD2012018，No.QN2013051）；西北农林科技大学博士启动基金（No.Z111021301）。 （）
