农业机械学报2018，Vol.49Issue(5)：57-64,8.DOI:10.6041/j.issn.1000-1298.2018.05.007
基于M-K聚类法的果树上下冠层体积比测算
Estimation of Upper and Lower Canopy Volume Ratio of Fruit Trees Based on M-K Clustering
摘要
Abstract
The volume of tree canopy provides theoretical basis for the orchard spray,and the application of airborne laser scanning is widely used in canopy volume measurement,but there is a problem of lack of canopy information.To solve this problem and improve the accuracy of tree canopy volume measurement,a method based on image processing to measure the tree upper and lower canopy volume ratio was proposed.A new M-K clustering method combining Mahalanobis distance and K-means algorithm was created to split the image target area and find the ratio of the volume of pixels in the upper and lower canopy by rotation integration method.The further research reduced the error (nearly 25.3％)measurement of unilateral canopy image processing on this basis.According to the estimation results of multiple images of different sides of the fruit tree by arithmetic mean method,M-K clustering method was modified,which became more accurate and stable.Totally 23 apple trees and 20 cherry trees were experimented in the orchard,and the results were compared with the artificial measurement results,which showed that the M-K clustering method was in good agreement with artificial measurement results with R2apple of 0.775 and R2cherry of 0.832.It can be used for the measurement of canopy volume ratio.关键词
果树冠层/体积比/图像处理/马氏距离/K-means算法Key words
fruit canopy/volume ratio/image processing/Mahalanobis distance/K-means algorithm分类
信息技术与安全科学引用本文复制引用
祁力钧,程一帆,程浈浈,杨知伦,吴亚垒,葛鲁振..基于M-K聚类法的果树上下冠层体积比测算[J].农业机械学报,2018,49(5):57-64,8.基金项目
国家重点研发计划项目(2017YFD0701400、2016YFD0200708) （2017YFD0701400、2016YFD0200708）
