摘要
[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.
[目的]研究选取稻飞虱为害后水稻叶片的有效特征波段，用于从大量成像光谱数据中快速识别和分类稻飞虱为害后的水稻叶片。[方法]实验采用多光谱成像系统对400-720 nm波段范围，每隔5 nm的稻飞虱为害后的水稻叶片进行多光谱成像。[结果]根据波段指数原理，计算得出波段515，510，710，555，630，535，505，530和595 nm具有较理想的波段指数值，这些波段信息量丰富、相关性小；实验通过两种分类方法分别对稻飞虱为害后的水稻叶片的分类精度予以计算，得出全波段和特征波段的分类精度均大于90.00%。[结论]这些选取的波段可以作为稻飞虱为害后水稻叶片的有效特征波段，可以用于从大范围农作物中快速识别和分类水稻叶片。
基金
Supported by National Natural Science Foundation of China under Grant(No.60968001,61168003)
Natural Science Foundation of Yunnan Province under Grant(No.2011FZ079,2009CD047)
National Training Programs of Innovation and Entrepreneurship for Undergraduates under Grant(No.201210681005,201310681004)~~
