森林病虫害监测中的无人机图像分割算法比较  

Comparison of algorithms for unmanned aerial vehicle image segmentation in monitoring forest diseases and insect pests

作　　者：费运巧 刘文萍[1] 骆有庆[2] 陆鹏飞[2] FEI Yunqiao;LIU Wenping;LUO Youqing;LU Pengfei(College of Information, Beijing Forestry University, Beijing 100083, China;College of Forestry, Beijing Forestry University, Beijing 100083, China)

机构地区：[1]北京林业大学信息学院,北京100083 [2]北京林业大学林学院,北京100083

出　　处：《计算机工程与应用》2017年第8期216-223,共8页Computer Engineering and Applications

基　　金：林业公益性行业科研专项经费资助(No.201404401)

摘　　要：以错分率、相对最终测量精度以及运行时间为评价标准,利用无人机采集的油松及沙棘正射图像为测试图像,对6种基于像素聚类及分水岭的图像分割算法的性能进行了定性分析及定量比较。实验结果表明,受灾林区图像的分割算法的性能与图像拍摄高度、噪声等因素密切相关。最后,给出了受灾林区无人机正射图像分割算法应用的指导性建议。Six image segmentation algorithms based on the pixel clustering and watershed thought are chosen for segmenting the orthographic images of Chinese pine and sea-buckthorn captured by unmanned aerial vehicle.As evaluation criteria of algorithms,misclassification error,relative ultimate measurement accuracy and running time are implemented to compare segmentation performance of each algorithm objectively and quantitatively.Experimental results demonstrate that the accuracy of each algorithm is closely related to the image capture height and noise.The conclusion can play a guidance role in selecting algorithm for stricken forest orthographic images segmentation.

关 键 词：森林病虫害监测 无人机正射图像 图像分割 基于像素的聚类 分水岭算法 性能评价 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]