本文選題：激光儀 + 聚類(lèi)算法��； 參考：《農(nóng)業(yè)工程學(xué)報(bào)》2017年S1期

【摘要】：精確的果樹(shù)三維冠層結(jié)構(gòu)是農(nóng)業(yè)科研人員進(jìn)行功能結(jié)構(gòu)模型研究的重要載體,該文提出一種快速、精確、自動(dòng)的果樹(shù)冠層葉片重建方法。首先根據(jù)帶葉果樹(shù)點(diǎn)云的局部和全局特征,建立橢球分層的點(diǎn)云密度收縮方法實(shí)現(xiàn)器官點(diǎn)云分離,然后利用鄰近傳播主成分分析算法實(shí)現(xiàn)葉片特征參數(shù)的求解,利用Laplacian收縮算法實(shí)現(xiàn)冠層骨架點(diǎn)的連通,從而實(shí)現(xiàn)冠層葉片的快速自動(dòng)重建。最后利用C++及Point Cloud Library(PCL)點(diǎn)云庫(kù),開(kāi)發(fā)果樹(shù)葉片點(diǎn)云冠層自動(dòng)重建系統(tǒng),對(duì)蘋(píng)果樹(shù)、柑橘樹(shù)等不同類(lèi)型果樹(shù)進(jìn)行算法驗(yàn)證,結(jié)果表明該方法能夠正確識(shí)別出的葉片數(shù)占冠層總?cè)~片數(shù)的90%以上,葉面積指數(shù)的正確率大于95%,葉片傾角偏離5?以?xún)?nèi)的葉片數(shù)占總?cè)~片數(shù)的90%以上。該方法得到了較好的可視化效果和葉冠三維重建精度,可為后期樹(shù)體冠層內(nèi)光合作用的研究、整形修剪、農(nóng)業(yè)仿真試驗(yàn)等提供參考。
[Abstract]:The accurate three-dimensional canopy structure of fruit trees is an important carrier for agricultural researchers to study the functional structure model. In this paper, a fast, accurate and automatic method for canopy leaf reconstruction of fruit trees is proposed. Firstly, according to the local and global characteristics of point cloud in fruit trees with leaves, an ellipsoidal and stratified point cloud density contraction method is established to separate organs from point clouds, and then the method of neighborhood propagation principal component analysis is used to solve the characteristic parameters of leaves. The Laplacian shrinkage algorithm is used to realize the connectivity of the canopy skeleton, so that the canopy blade can be reconstructed automatically. Finally, using C and Point Cloud Library, an automatic canopy reconstruction system is developed to verify the algorithm of apple trees, citrus trees and other different types of fruit trees, such as apple trees, citrus trees and other different types of fruit trees. The results show that the number of leaves can be correctly identified by this method, which accounts for more than 90% of the total leaf number in the canopy, and the accuracy of leaf area index is greater than 95%, and the angle of leaf inclination deviates from 5%. The number of leaves within the total number of leaves accounted for more than 90%. This method has better visualization effect and 3D reconstruction accuracy of leaf crown, which can be used as reference for the study of photosynthesis in canopy layer, plastic pruning and agricultural simulation experiment.
【作者單位】： 北京林業(yè)大學(xué)信息學(xué)院;國(guó)家農(nóng)業(yè)信息化工程技術(shù)研究中心;北京農(nóng)業(yè)信息技術(shù)研究中心;數(shù)字植物北京重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家“863”高技術(shù)研究發(fā)展計(jì)劃課題(2013AA102405) 北京市科技新星資助項(xiàng)目(Z131101000413022) 北京市農(nóng)林科學(xué)院科技創(chuàng)新團(tuán)隊(duì)(JNKYT201604)聯(lián)合資助
【分類(lèi)號(hào)】：S66;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳海嘯;陸聲鏈;徐踐;;果樹(shù)冠層形態(tài)特征測(cè)量與分析研究進(jìn)展[J];中國(guó)農(nóng)業(yè)科技導(dǎo)報(bào);2016年06期

2 王傳宇;郭新宇;溫維亮;杜建軍;肖伯祥;;田間光照條件下應(yīng)用半球圖像解析玉米冠層結(jié)構(gòu)參數(shù)[J];農(nóng)業(yè)工程學(xué)報(bào);2016年04期

3 溫維亮;郭新宇;盧憲菊;王勇健;趙德達(dá);廖維華;;玉米器官三維模板資源庫(kù)構(gòu)建[J];農(nóng)業(yè)機(jī)械學(xué)報(bào);2016年08期

4 溫維亮;郭新宇;王勇健;李超;陸聲鏈;;葡萄樹(shù)地上部形態(tài)結(jié)構(gòu)數(shù)據(jù)獲取方法[J];農(nóng)業(yè)工程學(xué)報(bào);2015年22期

5 張德嘉;梁爽;張晨;賈金原;;基于增強(qiáng)PyrLK光流法的三維樹(shù)木骨架重建方法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2015年07期

6 王果;沙從術(shù);王健;;考慮局部點(diǎn)云密度的建筑立面自適應(yīng)分割方法[J];激光與光電子學(xué)進(jìn)展;2015年06期

7 張冬;云挺;薛聯(lián)鳳;羅毅;;復(fù)雜拓?fù)浣Y(jié)構(gòu)的樹(shù)木枝干重建算法[J];南京師大學(xué)報(bào)(自然科學(xué)版);2015年01期

8 王勇健;溫維亮;郭新宇;趙春江;;基于點(diǎn)云數(shù)據(jù)的植物葉片三維重建[J];中國(guó)農(nóng)業(yè)科技導(dǎo)報(bào);2014年05期

9 王兆豐;閆鑌;童莉;陳健;李建新;;自適應(yīng)鄰域尺寸選擇的點(diǎn)云法向量估計(jì)算法[J];紅外與激光工程;2014年04期

10 王志彬;王開(kāi)義;張水發(fā);劉忠強(qiáng);穆翠霞;;基于K-means聚類(lèi)和橢圓擬合方法的白粉虱計(jì)數(shù)算法[J];農(nóng)業(yè)工程學(xué)報(bào);2014年01期

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

1 駱健;蔣e，

本文編號(hào)：1971778