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作 者:周晓琳 安如[1] 陈跃红 艾泽天 黄理军 ZHOU Xiaolin;AN Ru;CHEN Yuehong;AI Zetian;HUANG Lijun(School of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China)
机构地区:[1]河海大学地球科学与工程学院,南京211100
出 处:《亚热带资源与环境学报》2018年第4期85-92,共8页Journal of Subtropical Resources and Environment
基 金:国家自然科学基金资助项目(41271361)
摘 要:草原鼠洞的识别定位可以为鼠害的监测、预测和防治等提供科学参考,因此,如何快速且准确地识别草地鼠洞成为亟需解决的问题。选取玛多县典型区作为研究区,利用可见光波段无人机影像,研究并建立了面向对象的模板匹配法和支持向量机法的草地鼠洞自动识别方法。模板匹配法是在多尺度分割的影像中选取不同种类的鼠洞对象并生成匹配模板,接着进行目标检测并产生初始结果,最后构建光谱、几何和纹理特征库对检测结果进行筛选。支持向量机法首先采集鼠洞训练样本并优化分类特征空间,然后采用支持向量机分类器监督分类得到鼠洞识别结果。对2种方法的识别结果进行精度评价与分析表明:2种方法的总体精度均较高,适用于三江源区草原鼠洞的精准识别。基于面向对象的模板匹配法比支持向量机法的总体识别精度整体高1%,错分误差低3%,识别效果较好。Identification and location of rat holes in grassland provide scientific reference for the monitoring,prediction and prevention of rodent.How to identify rat holes in grassland quickly and accurately becomes an urgent problem.Based on visible image acquired by unmanned aerial vehicles(UAVs)in a typical area of Madoi County,this study used the Object-oriented Template Matching(OTM)method and Support Vector Machine(SVM)method to identify its rat holes in grassland automatically.OTM method is to select different kinds of rat-hole objects from multi-scale segmentation images.Then it generates matching templates,target detection and initial results generated.Finally the spectral,geometric and texture features of the target rat-hole objects are extracted to construct a feature knowledge base and to screen the detection results.SVM method firstly collects the training samples and optimizes the classification feature space.Then SVM classifier is used to supervise the classification to get the rat-hole recognition result.The accuracy evaluation and analysis of the two methods show that they have high overall accuracy,and are suitable for the accurate identification of rat holes in grassland of"Three-River Headwaters"region.The overall identification accuracy of object-oriented template matching method is1%higher than the other one,and the commission error is3%lower showing slightly better effect of identification.
分 类 号:TP79[自动化与计算机技术—检测技术与自动化装置]
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