一种改进的图像拼接技术及其在无人机病虫害检测中的应用  

An Improved Image Mosaic Technique and Its Application in UAV Pest and Disease Detection

作　　者：蔺瑶 曾晏林 贺壹婷 费加杰 黎强 杨毅[1] LIN Yao;ZENG Yanlin;HE Yiting;FEI Jiajie;LI Qiang;YANG Yi(School of Big Data,Yunnan Agricultural University,Kunming 650201,China)

机构地区：[1]云南农业大学大数据学院,云南昆明650201

出　　处：《云南师范大学学报（自然科学版）》2023年第1期34-39,共6页Journal of Yunnan Normal University:Natural Sciences Edition

基　　金：云南省重大科技专项资助项目(A3032021043002)。

摘　　要：为解决ORB(oriented FAST and rotated BRIEF)算法提取的特征点分布不均匀且可能重叠的问题,在ORB算法的基础上引入了四叉树结构实现特征点均匀分配,使用KNN算法进行特征点粗略匹配,通过RANSAC算法去除虚假匹配点以获得完整的病虫害图像.实验结果表明,与ORB算法和SIFT相比,新算法匹配精度分别提高了8%以上和3%以上.In order to solve the problem of uneven distribution of feature points extracted by ORB(oriented FAST and rotated BRIEF)algorithm and possible overlap,a quadtree structure is introduced on the basis of ORB algorithm to achieve uniform distribution of feature points,KNN algorithm is used for rough matching of feature points,and false matching points are removed by RANSAC algorithm to obtain a complete pest and disease images.The experimental results show that this paper improves the matching accuracy by more than 8%and 3%compared with the ORB algorithm and SIFT,respectively.

关 键 词：ORB算法 四叉树 RANSAC算法 无人机 病虫害 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]