野外自然状况下蝗虫种群动态监测自适应模型研究

项目名称： 野外自然状况下蝗虫种群动态监测自适应模型研究

项目编号： No.31471762

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 农业科学

项目作者： 李林

作者单位： 中国农业大学

项目金额： 85万元

中文摘要： 本项目以蝗虫为研究对象，基于计算机视觉技术和多光谱图像融合技术，研究在野外自然状况下蝗虫种群动态的自动化监测新方法。本项目首先在深入研究蝗虫光谱特征和图像特征的基础上，建立多模态蝗虫特征数据库；然后，构建基于可见光和近红外的多光谱计算机视觉系统，建立多源图像融合模型和图像背景提取模型，结合蝗虫形态特征和行为特性,获取蝗虫目标相关信息，并依据多模态蝗虫特征数据库以及相关模型调用规则，建立蝗虫虫口密度计算、种类识别和龄期鉴定的综合自适应模型，进行蝗虫种类和龄期的识别以及虫口密度的计算，实现野外自然状况下蝗虫种群动态的自动化监测。本项目研究成果不仅能够为野外蝗虫监测奠定一定理论基础，而且能够为其它昆虫自动化监测提供方法学参考，具有重要的理论和实践意义。

中文关键词： 蝗虫；虫口密度；发育进度；野外监测；多源图像融合

英文摘要： With locusts as the research object,this project,based on the computer vision technology and the multi-source images fusion technology,developes a new automatic monitoring method for the locust population dynamics. Firstly,this study will further research the spectral features and image characters about the locust, based on which to establish the multi-modality locust feature database.Then, the project aims to realize the following major research targets step by step: building multi-spectral computer-vision system on the basis of the visible light and near infra-red spectrum; establishing the multi-source images fusion model and the image background extraction model; obtaining relevant information about the targeted locust in aspects of morphological and behavior characteristics; as well as setting up an integrated self-adaptive model in accordance with the multi-modality locust feature database and related model call rules, which includes the population calculation, species identification and instars discrimination, with an aim to get the result about the population, species and instars of the locust. Finally, the automatic monitoring of the locust population dynamics in field will be realized. The results of this study not only forms the theoretical foundation for the locust automatic monitoring in field, but also provides methodological references to other insect monitoring approaches, which is of great important significance both in theoretical and practical perspectives.

英文关键词： Locust;Population Density of Locust;Development Progress;Field Monitore;Multi-source Image Fusion