胡心雨,冉茂,葉協(xié)鋒,李家輝,肖慶禮,王紅鋒,劉琳琳,左萬(wàn)琦,張芊*
研究簡(jiǎn)報(bào)
基于三維點(diǎn)云的烤煙三維模型構(gòu)建及株型分析
胡心雨1,冉茂2,葉協(xié)鋒1,李家輝1,肖慶禮3,王紅鋒2,劉琳琳1,左萬(wàn)琦4,張芊1*
1 河南農(nóng)業(yè)大學(xué)煙草學(xué)院,國(guó)家煙草栽培生理生化研究基地,煙草行業(yè)煙草栽培重點(diǎn)實(shí)驗(yàn)室,鄭州市金水區(qū)文化路95號(hào) 450002;2 重慶煙草科學(xué)研究所,重慶市北碚區(qū)天生街道天生路2號(hào) 400715;3 重慶中煙工業(yè)有限責(zé)任公司,重慶市南岸區(qū)南坪東路2號(hào) 400060;4 重慶市煙草公司酉陽(yáng)分公司,重慶市酉陽(yáng)縣桃花源街道桃花源大道中路87號(hào) 409800
【】為了構(gòu)建煙株的三維模型、提取烤煙株型信息?!尽坎捎媒Y(jié)構(gòu)光掃描儀獲取烤煙的三維點(diǎn)云數(shù)據(jù),經(jīng)過(guò)點(diǎn)云配準(zhǔn)、點(diǎn)云去噪以及孔洞修補(bǔ)等步驟后構(gòu)建了烤煙的三維模型,并對(duì)烤煙株型參數(shù)進(jìn)行了誤差估計(jì)。【】利用該方法構(gòu)建的烤煙三維模型能夠精確還原烤煙的形態(tài)結(jié)構(gòu),葉長(zhǎng)、葉寬和株高的機(jī)器測(cè)量值和人工測(cè)量值擬合方程的2均達(dá)0.8以上?!尽炕谌S點(diǎn)云構(gòu)建的烤煙三維模型精度高,為煙草科研和煙葉生產(chǎn)提供了一種高精度的烤煙株型判別方法。
烤煙;結(jié)構(gòu)光;三維模型;三維掃描
株型對(duì)烤煙生長(zhǎng)發(fā)育極為重要,且影響煙葉的品質(zhì)[1]。傳統(tǒng)研究多通過(guò)田間測(cè)定煙株的農(nóng)藝性狀來(lái)確定烤煙株型參數(shù)[2-3]。隨著智慧農(nóng)業(yè)的興起,基于虛擬仿真技術(shù)構(gòu)建的植株三維模型,已成為研究包括烤煙在內(nèi)的多種植物株型的重要方法[4-9]。構(gòu)建植株三維模型常用的方法包括L-系統(tǒng)[10-12]、參考軸AMAP、分 形[13]以及三維掃描技術(shù)[14],其中三維掃描技術(shù)是采集植株空間結(jié)構(gòu)信息、構(gòu)建三維模型的最有效方式。
前人多利用基于激光雷達(dá)的掃描儀對(duì)煙草進(jìn)行三維建模,但該方法耗時(shí)長(zhǎng)且精度有限。本研究利用Artec掃描儀建立煙株的三維模型,利用三維模型獲取烤煙株型參數(shù),并與田間實(shí)測(cè)數(shù)據(jù)進(jìn)行比較,從而評(píng)價(jià)該方法的精度和可用性,以期為烤煙株型研究提供新的解決方案。
田間試驗(yàn)于2020年在重慶市酉陽(yáng)縣龔灘鎮(zhèn)楊柳村(北緯28°98′23″,東經(jīng)108°39′38″)進(jìn)行,供試品種為當(dāng)?shù)刂髟云贩NK326,行距1.2 m,株距0.5 m,試驗(yàn)地土壤pH 4.8,有機(jī)碳含量16.81 g/kg,全氮含量1.55 g/kg,堿解氮含量86.74 mg/kg,速效鉀含量259.83 mg/kg,速效磷含量85.07 mg/kg。于2020年5月初移栽,苗齡約55 d,采用小苗膜下移栽,施氮量為90 kg/hm2,在煙株現(xiàn)蕾開(kāi)花后打頂,各種管理措施均與當(dāng)?shù)馗弋a(chǎn)煙田保持一致。
采用Artec Eva三維掃描儀(美國(guó)阿泰克公司)獲取烤煙三維模型,該儀器是一種便攜式三維掃描設(shè)備,分辨率0.5 mm,3D數(shù)據(jù)精度可達(dá)0.1 mm,掃描時(shí)儀器和掃描面保持垂直并勻速移動(dòng),且距離在0.4~1 m。
1.2.1 掃描精度的評(píng)估
為了對(duì)該設(shè)備的掃描精度進(jìn)行評(píng)估,在烤煙生長(zhǎng)的各個(gè)時(shí)期對(duì)煙株進(jìn)行整體掃描,并將烤煙株高、葉長(zhǎng)及葉寬的計(jì)算值和測(cè)量值進(jìn)行對(duì)比以評(píng)估三維掃描的精度。用三維掃描儀的配套軟件對(duì)掃描得到的模型進(jìn)行處理并讀取煙株最高點(diǎn)和最低點(diǎn)的坐標(biāo),計(jì)算出兩點(diǎn)之間的距離,即為株高;葉片正面自莖葉連接處至葉尖的直線長(zhǎng)度即為葉片長(zhǎng)度;葉面最寬處與主脈的垂直長(zhǎng)度即為葉片寬度。
1.2.2 烤煙三維模型的獲取
分別于移栽后30 d(團(tuán)棵期)、70 d(打頂后)和80 d(圓頂期),選取18株烤煙進(jìn)行三維掃描。將煙株連根拔起放入花盆中并移至室內(nèi),及時(shí)對(duì)煙株進(jìn)行掃描,為避免掃描過(guò)程中煙株萎蔫造成誤差,煙株應(yīng)保持根部濕潤(rùn),且掃描過(guò)程中避免煙株晃動(dòng)而造成數(shù)據(jù)丟失。
1.2.3 烤煙株型指標(biāo)的獲取
參考前人烤煙株型的劃分標(biāo)準(zhǔn)[15]。對(duì)移栽后80 d烤煙株型指標(biāo)進(jìn)行提取并對(duì)烤煙株型進(jìn)行判定。
1.3.1 原理
本研究采用的Artec Eva三維掃描儀是結(jié)構(gòu)光三維掃描儀,其由一個(gè)光柵發(fā)射鏡頭和一個(gè)信息采集鏡頭組成。發(fā)射鏡頭將光柵投影到物體表面,由于物體具有高度差,光柵會(huì)因此發(fā)生形變,將光柵的形變轉(zhuǎn)化為光柵相位高度的變化,由此得到物體攜帶的三維的信息,并構(gòu)建物體的三維模型。
圖1 結(jié)構(gòu)光三維掃描儀原理示意圖
1.3.2 數(shù)據(jù)處理
點(diǎn)云數(shù)據(jù)指在一組三維坐標(biāo)系統(tǒng)中的向量合集,掃描資料以點(diǎn)的形式記錄,每一個(gè)點(diǎn)包含三維坐標(biāo),其中一些含有顏色信息或反射強(qiáng)度信息。對(duì)掃描得到的點(diǎn)云數(shù)據(jù)進(jìn)行預(yù)處理,主要包括配準(zhǔn)、刪除離群噪點(diǎn)、孔修補(bǔ)等,防止個(gè)別誤差點(diǎn)對(duì)三維模型的精度造成影響。點(diǎn)云處理前后情況見(jiàn)圖2。
圖2 點(diǎn)云預(yù)處理前(左)后(右)烤煙模型對(duì)比
1.3.2.1 點(diǎn)云配準(zhǔn)
點(diǎn)云配準(zhǔn)是指將不同掃描幀的烤煙三維點(diǎn)云數(shù)據(jù)統(tǒng)一到一個(gè)坐標(biāo)系下,進(jìn)而獲取煙株各點(diǎn)真實(shí)三維坐標(biāo)的過(guò)程[16]。點(diǎn)云配準(zhǔn)包含基于靶標(biāo)的配準(zhǔn)和基于形狀的配準(zhǔn)2種方式,即通過(guò)尋找不同掃描幀之間的同名點(diǎn),然后將矩陣帶入數(shù)學(xué)模型中進(jìn)行計(jì)算和轉(zhuǎn)換,即可得到統(tǒng)一在同一坐標(biāo)系下的坐標(biāo)。本研究采用Artec Studio進(jìn)行配準(zhǔn),其中包含粗略配準(zhǔn)、精細(xì)配準(zhǔn)和整體配準(zhǔn),由于獲取的點(diǎn)云數(shù)量大,通過(guò)靶標(biāo)和形狀的匹配來(lái)縮小搜索范圍,減少計(jì)算量。
1.3.2.2 刪除離群噪點(diǎn)
刪除離群噪點(diǎn),即點(diǎn)云去噪。在進(jìn)行三維掃描時(shí),由于三維掃描儀本身的誤差以及操作和外界環(huán)境的不可控性,會(huì)產(chǎn)生一些誤差噪點(diǎn)[17],這些噪點(diǎn)類型多樣且分布無(wú)規(guī)律。噪點(diǎn)的存在影響模型的精度,本研究利用Artec Studio的離群噪點(diǎn)去除功能,對(duì)半徑r和點(diǎn)數(shù)量t進(jìn)行設(shè)定,對(duì)于點(diǎn)云中的點(diǎn)a,若以點(diǎn)a為球心、r為半徑的球體內(nèi)點(diǎn)的數(shù)量小于t,則將a定義為離群噪點(diǎn)并對(duì)其進(jìn)行剔除。
1.3.2.3 孔修補(bǔ)
由于煙葉相互遮擋且煙葉表面存在不規(guī)則褶皺,三維掃描儀發(fā)射的光不能被反射導(dǎo)致缺失數(shù)據(jù),造成點(diǎn)云數(shù)據(jù)存在孔洞。孔洞讓模型不完整,并且影響后續(xù)數(shù)據(jù)的提取,導(dǎo)致精度降低[18],因此,孔洞的修補(bǔ)顯得格外重要。本研究采用配套軟件中孔修復(fù)功能對(duì)孔洞進(jìn)行修復(fù),其原理為基于散亂點(diǎn)云的孔洞修復(fù),即先識(shí)別點(diǎn)云孔洞的邊界,進(jìn)而建立孔洞的曲面函數(shù)以實(shí)現(xiàn)孔洞的修復(fù)。
利用 Mircosoft Excel 2010 進(jìn)行數(shù)據(jù)處理和圖表繪制,Artec Studio 15.0 及GeomagicWrap進(jìn)行三維模型處理。
由于煙株的大小及煙株形態(tài)存在差異,掃描一株煙的耗時(shí)有所不同,但通常在5~20 min,就本研究而言,在團(tuán)棵期(移栽后30 d)煙株較小且有效葉片數(shù)較少,掃描一株煙的時(shí)間在5~8 min,而圓頂期(移栽后80 d)掃描一株煙需要約20 min。
為對(duì)三維掃描的精度進(jìn)行評(píng)估,通過(guò)在大田內(nèi)人工測(cè)量烤煙株高、葉長(zhǎng)和葉寬,并將其分別與三維模型數(shù)據(jù)進(jìn)行比較。對(duì)株高、葉長(zhǎng)以及葉寬的人工測(cè)量值和三維模型值的吻合程度進(jìn)行分析,由圖3可知,株高、葉長(zhǎng)及葉寬的人工測(cè)量值和計(jì)算值吻合程度較好,株高2達(dá)0.9866,且RMSE值為1.83;葉長(zhǎng)2為0.8602, RMSE值為3.85;葉寬2為0.8318,RMSE值為2.79。葉長(zhǎng)及葉寬的吻合程度略低于株高,是由于煙葉在自然生長(zhǎng)狀態(tài)下表面存在褶皺,人工測(cè)定時(shí)存在一定誤差。
圖3 基于三維掃描儀的測(cè)量值和人工測(cè)量值的比較
圖4 不同時(shí)期的烤煙K326三維可視化模型
Fig. 4 Three-dimensional visualization model of flue-cured tobacco K326 in different periods
經(jīng)預(yù)處理后得到的烤煙K326三維模型,可提取出烤煙株型相關(guān)的指標(biāo)并以此對(duì)烤煙株型進(jìn)行判斷(表1)??緹烱326三維可視化模型如圖5所示,移栽后80 d煙株呈現(xiàn)長(zhǎng)筒形,與利用模型獲得的判定結(jié)果吻合。
表1 烤煙K326株型判定
Tab.1 Determination of plant type of flue-cured tobacco K326
圖5 烤煙K326株型示意圖
本研究采用手持式結(jié)構(gòu)光三維掃描儀快速獲取點(diǎn)云數(shù)據(jù),通過(guò)點(diǎn)云配準(zhǔn)、點(diǎn)云去噪和孔洞修補(bǔ)等過(guò)程建立烤煙三維模型,并對(duì)其進(jìn)行可視化和株型參數(shù)提取。通過(guò)株高、葉長(zhǎng)和葉寬等指標(biāo)進(jìn)行誤差估計(jì),結(jié)果顯示,三維掃描的精度較高,人工測(cè)量值和機(jī)器測(cè)量值擬合的2均達(dá)0.8以上,利用提取的數(shù)據(jù)信息進(jìn)行烤煙K326的株型判斷(長(zhǎng)筒形),符合K326的株型特征。本研究構(gòu)建的烤煙三維模型可以準(zhǔn)確地獲取烤煙株型特征參數(shù)。
魏學(xué)禮等[19]應(yīng)用徠卡ScanStation2和Vivid9i兩款三維激光掃描儀對(duì)煙株進(jìn)行掃描發(fā)現(xiàn)只能對(duì)植株進(jìn)行整體掃描,葉片之間相互遮擋,大量細(xì)節(jié)無(wú)法顧及,從而使獲取的三維信息出現(xiàn)明顯偏差;郭焱等[20]采用FastSCAN三維激光掃描儀對(duì)烤煙植株進(jìn)行掃描,由于綠葉會(huì)吸收儀器發(fā)射的紅光導(dǎo)致不能正常地返回植物信息,故噴灑爽身粉以解決此問(wèn)題,但爽身粉很難噴灑均勻,且易被風(fēng)吹散,影響數(shù)據(jù)采集的精度;王劍等[21]指出FastSCAN三維激光掃描儀可受磁場(chǎng)的干擾使探棒無(wú)法定位,從而影響其精度。而本研究中采用的基于結(jié)構(gòu)光掃描技術(shù)構(gòu)建的烤煙三維模型具有較高的精度和數(shù)據(jù)獲取效率,且與FastSCAN等基于激光雷達(dá)的掃描儀不同,不受掃描對(duì)象顏色的影響且不受磁場(chǎng)干擾。此外,本研究中利用Artec掃描儀相較于使用FastSCAN對(duì)煙株進(jìn)行掃描的耗時(shí)大大縮短。
植物表型是其遺傳特性與環(huán)境交互的三維表達(dá)[22]。煙株三維模型作為其表型信息的載體,為產(chǎn)量預(yù)測(cè)、群體性狀監(jiān)測(cè)、病蟲(chóng)害監(jiān)測(cè)預(yù)警等提供了信息支撐,是智慧煙草的重要基礎(chǔ)。利用株型等來(lái)自烤煙三維模型的表型信息能夠建立煙草的表型-生長(zhǎng)-品質(zhì)的預(yù)測(cè)模型,實(shí)現(xiàn)基于表型信息的烤煙生長(zhǎng)發(fā)育過(guò)程監(jiān)測(cè)和分析,為烤煙養(yǎng)分監(jiān)測(cè)和成熟采收提供指導(dǎo)和建議,相關(guān)研究將在未來(lái)逐步開(kāi)展。本研究限于條件僅對(duì)K326進(jìn)行了數(shù)據(jù)采集、建模及驗(yàn)證,未來(lái)計(jì)劃在更多烤煙品種上推廣應(yīng)用。此外,三維掃描獲取的煙株點(diǎn)云數(shù)據(jù)量大,受限于計(jì)算機(jī)性能,數(shù)據(jù)后期的處理以及建模耗時(shí)相對(duì)較長(zhǎng),需要進(jìn)一步優(yōu)化以提高數(shù)據(jù)處理效率。
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Study on the construction of 3D model of flue-cured tobacco based on 3D point cloud
HU Xinyu1, RAN Mao2, YE Xiefeng1, LI Jiahui1, XIAO Qingli3, WANG Hongfeng2, LIU Linlin1, ZUO Wanqi4, ZHANG Qian1*
1 Tobacco College of Henan Agricultural University, National Research Base of Tobacco Cultivation Physiology and Biochemistry, Key Laboratory of Tobacco Cultivation of Tobacco Industry, Zhengzhou 450002, China; 2 Chongqing Tobacco Science Research Institute, Chongqing 400715, China; 3 Chongqing China Tobacco Industry Co., Ltd., Chongqing 400060, China; 4 Chongqing Tobacco Company Youyang Branch, Chongqing Youyang 409800, China
This study aims to construct a three-dimensional model of tobacco plants and extract flue-cured tobacco plant type information.By using a structured light scanner to obtain three-dimensional point cloud data of flue-cured tobacco and going through the steps of point cloud registration, point cloud denoising, and hole repair, a three-dimensional modeling method for flue-cured tobacco based on structured light technology is proposed in this study. The three-dimensional model of flue-cured tobacco was constructed, and the error estimation of flue-cured tobacco plant type parameters was carried out.The results show that the three-dimensional model of flue-cured tobacco constructed by this method can accurately restore the morphology and structure of flue-cured tobacco, where R2of fitting equations of the machine-measured and artificially measured values of leaf length, leaf width and plant height are above 0.8, indicating higher accuracy.The three-dimensional model of flue-cured tobacco constructed based on three-dimensional point cloud has high accuracy. It provides a high-precision method for identifying flue-cured tobacco plant types.
flue-cured tobacco; structured light; three dimensional model; 3D scanning
Corresponding author. Email:zhangqian225@163.com
胡心雨,冉茂,葉協(xié)鋒,等.基于三維點(diǎn)云的烤煙三維模型構(gòu)建及株型分析[J]. 中國(guó)煙草學(xué)報(bào),2022,28(3).HU Xinyu, RAN Mao, YE Xiefeng, et al. Study on the construction of 3D model of flue-cured tobacco based on 3D point cloud[J]. Acta Tabacaria Sinica, 2022,28(3). doi: 10.16472/j.chinatobacco. 2021.T0129
重慶市煙草公司科技項(xiàng)目“云產(chǎn)卷煙原料生產(chǎn)技術(shù)體系研究與構(gòu)建”(A20201NY01-1303);重慶市煙草公司科技項(xiàng)目“利群卷煙原料生產(chǎn)技術(shù)體系研究與構(gòu)建”(A20201NY01-1304);重慶市煙草公司科技項(xiàng)目“天子卷煙原料生產(chǎn)技術(shù)體系研究與構(gòu)建”(A20201NY01-1306)
胡心雨(1998—),碩士研究生,研究方向?yàn)闊煵菰耘嗌砩?,Tel:0371-63555763,Email:h18638140320@163.com
張芊(1980—),博士,研究方向?yàn)闊煵菪畔W(xué),Tel:0371-63555763,Email:zhangqian225@163.com
2021-07-31;
2022-02-11