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基于顏色取樣的蘋果樹枝干點云數(shù)據(jù)提取方法
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國家重點研發(fā)計劃項目(2017YFD0700503)和河北省高等學(xué)??茖W(xué)技術(shù)研究項目(QN2017417)


Point Cloud Extraction of Apple Tree Canopy Branch Based on Color Sampling
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    摘要:

    為了快速提取蘋果樹冠層枝干三維點云數(shù)據(jù),,以不同生長時期蘋果樹冠層彩色點云數(shù)據(jù)為研究對象,,提出了基于顏色取樣的蘋果樹枝干點云數(shù)據(jù)提取方法,。首先,提出了蘋果樹冠層彩色點云獲取方法,,利用Trimble TX8型地面三維激光掃描儀獲取冠層點云數(shù)據(jù),,同軸全景攝像機獲取彩色全景圖,采用貼圖方法著色點云數(shù)據(jù),;然后,,提取全景圖像蘋果樹冠層區(qū)域R、G,、B顏色分量信息,,根據(jù)其分布規(guī)律建立枝干部分自適應(yīng)分割閾值,并根據(jù)顏色閾值刪除冠層中非枝干部分彩色點云數(shù)據(jù),;最后,,在Geomagic軟件中經(jīng)過封裝—創(chuàng)建流形—編輯多邊形—填充孔—光滑等一系列操作重建枝干三維模型。蘋果樹提取枝干點云數(shù)據(jù)實驗結(jié)果表明,,本文方法點云刪除率為75.74%,,相對于人工枝干點云數(shù)據(jù)提取,,側(cè)枝數(shù)量平均準確率為93.34%,效率提高200倍以上,,大大縮短了冠層枝干三維重建時間,。本研究成果可為有葉蘋果樹枝干動力學(xué)模型建立提供技術(shù)基礎(chǔ)。

    Abstract:

    Construction of 3D model of tree is a longterm research hotspot in botany, computer graphics, and architecture. And tree canopy branch reconstruction is an important component in the canopy dynamics analysis. The emergence of terrestrial laser scanners has accelerated this reconstruction process. To quickly reconstruct the canopy branch model, it is necessary to delete a large number of nonbranched interference point clouds. Taking the canopy of apple tree in the maturity growth stage as the research object, a method of colorbased sampling apple tree canopy trunk point cloud extraction was proposed. Firstly, the apple tree canopy color point cloud acquisition method was proposed. Trimble TX8 and coaxial panoramic camera were selected as the data acquisition device to acquire the apple canopy color point cloud data. Point clouds and color panoramic photos were matched in Realworks software, and color point clouds were get. Then, the color information R, G and B in the panoramic image was extracted. The adaptive segmentation threshold was established according to the distribution rules of R, G and B in the panoramic image branch area. Color point cloud data of the nonbranch part in the canopy was deleted according to the threshold. Finally, the 3D branch model was reconstructed in the Geomgic software. The process was followed by a series of operations, such as wrap, manifold creation, polygon editing, hole filling and smoothing. The experimental results of the apple tree branch extraction point cloud data showed that the point cloud deletion rate of this method was 75.74%. Compared with the artificial branch point cloud data extraction, the side branch accuracy rate was 93.34%, and the efficiency was improved by more than 200 times, shortening the threedimensional reconstruction time of canopy branches. In this way, the results of this study can provide a basis for studying the canopy structure analysis and the establishment of the branching dynamics model of the leafy apple tree.

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郭彩玲,劉剛.基于顏色取樣的蘋果樹枝干點云數(shù)據(jù)提取方法[J].農(nóng)業(yè)機械學(xué)報,2019,50(10):189-196. GUO Cailing, LIU Gang. Point Cloud Extraction of Apple Tree Canopy Branch Based on Color Sampling[J]. Transactions of the Chinese Society for Agricultural Machinery,2019,50(10):189-196.

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  • 收稿日期:2019-05-22
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  • 在線發(fā)布日期: 2019-10-10
  • 出版日期: 2019-10-10
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