Improved Rotation Kernel Transformation Directional Feature for Recognition of Wheat Stripe Rust and Powdery Mildew
文献类型： 外文期刊
作者： Wang, Liwen 1 ; Dong, Fangmin 1 ; Guo, Qing 1 ; Nie, Chenwei 2 ; Sun, Shuifa 1 ;
作者机构： 1.China Three Gorges Univ, Inst Intelligent Vis & Image Informat, Yichang 443002, Peoples R China
2.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词： Stripe rust and powdery mildew;IRKT directional feature;Directional distribution parameter;Disease recognition
期刊名称：2014 7TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP 2014)
ISSN：
年卷期： 2014 年
页码：
收录情况： SCI
摘要： To overcome the problem of lacking apparent features, e.g. color or shape, in the process of identifying wheat stripe rust from powdery mildew using computer vision algorithms, a novel directional feature based on Improved Rotation Kernel Transformation (IRKT) is proposed. IRKT can calculate the statistics of the direction distribution of infected leaf images in spatial domain. The statistics calculated from IRKT are insensitive to noise and can lead to a good description of directional distribution of object, which is suitable for the recognition of wheat stripe rust and powdery mildew and provides a novel method to represent other plant disease. As showed in experimental results, the proposed IRKT directional feature is fit for the recognition of wheat stripe rust and powdery mildew, and the accuracy can achieve 97.5%.
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