基于RGB-D相机的玉米茎粗测量方法
为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色图像和深度图像.首先,根据玉米与背景的颜色差异,对图像进行自动阈值分割,提取图像中感兴趣区域内的信息;利用形态学'开'操作剔除图像中的噪声,得到玉米茎杆的主干.其次,对茎杆主干进行骨架化操作,检测骨架的交叉点和末端点,确定茎杆的待测量部位.然后,对该部位的点云数据进行去噪、聚类、椭圆拟合操作,得到椭圆的长轴和短轴,获得玉米的茎粗.对20株玉米进行测试,结果表明:茎粗长轴的平均测量误差为3.31...
Saved in:
| Published in | 农业工程学报 Vol. 33; no. z1; pp. 170 - 176 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083%农业部农业信息获取技术重点实验室,北京,100083
2017
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2017.z1.026 |
Cover
| Abstract | 为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色图像和深度图像.首先,根据玉米与背景的颜色差异,对图像进行自动阈值分割,提取图像中感兴趣区域内的信息;利用形态学'开'操作剔除图像中的噪声,得到玉米茎杆的主干.其次,对茎杆主干进行骨架化操作,检测骨架的交叉点和末端点,确定茎杆的待测量部位.然后,对该部位的点云数据进行去噪、聚类、椭圆拟合操作,得到椭圆的长轴和短轴,获得玉米的茎粗.对20株玉米进行测试,结果表明:茎粗长轴的平均测量误差为3.31 mm,标准差为3.01 mm,平均测量相对误差为10.27%,茎粗短轴的平均测量误差为3.33 mm,标准差为2.39 mm,平均测量相对误差为12.71%.该研究可为作物表型参数的快速获取提供参考. |
|---|---|
| AbstractList | S126%TP391.41; 为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色图像和深度图像.首先,根据玉米与背景的颜色差异,对图像进行自动阈值分割,提取图像中感兴趣区域内的信息;利用形态学"开"操作剔除图像中的噪声,得到玉米茎杆的主干.其次,对茎杆主干进行骨架化操作,检测骨架的交叉点和末端点,确定茎杆的待测量部位.然后,对该部位的点云数据进行去噪、聚类、椭圆拟合操作,得到椭圆的长轴和短轴,获得玉米的茎粗.对20株玉米进行测试,结果表明:茎粗长轴的平均测量误差为3.31 mm,标准差为3.01 mm,平均测量相对误差为10.27%,茎粗短轴的平均测量误差为3.33 mm,标准差为2.39 mm,平均测量相对误差为12.71%.该研究可为作物表型参数的快速获取提供参考. 为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色图像和深度图像.首先,根据玉米与背景的颜色差异,对图像进行自动阈值分割,提取图像中感兴趣区域内的信息;利用形态学'开'操作剔除图像中的噪声,得到玉米茎杆的主干.其次,对茎杆主干进行骨架化操作,检测骨架的交叉点和末端点,确定茎杆的待测量部位.然后,对该部位的点云数据进行去噪、聚类、椭圆拟合操作,得到椭圆的长轴和短轴,获得玉米的茎粗.对20株玉米进行测试,结果表明:茎粗长轴的平均测量误差为3.31 mm,标准差为3.01 mm,平均测量相对误差为10.27%,茎粗短轴的平均测量误差为3.33 mm,标准差为2.39 mm,平均测量相对误差为12.71%.该研究可为作物表型参数的快速获取提供参考. |
| Abstract_FL | Stem diameters of maize are important phenotype parameters and can characterize the crop growth and lodging resistance, drawing more attentions from breeders. Traditional measurement about stem diameters is usually manual measurement, which is timeconsuming, laborious, and subject to human error. In order to rapidly measure stem diameters of maize in field, a method based on RGB-D (red, green, blue - depth) camera was proposed in this paper to extract stem diameters of maize. The color images and depth images of the maize plants at the small bell stage were captured by a RGB-D camera in field. First, maize stem was extracted by processing the color image. It was hard to recognize maize just according to the color differences in red, green and blue component between maize and background due to the illumination variations. To solve the problem, the component that represented the difference between green signals and illumination brightness was calculated and applied to segment maize with Otsu algorithm, and the binary image of maize was generated. And then erosion operation was conducted within region of interest to cut off the connection between little leaves and maize stem, and small regions were eliminated to remove weed and little leaves. The largest region of maize was saved after dilation operation. After that, skeletonization was conducted for main stem. There were crossing points at the points of contact between leaves and stem, and ending points at the points of contact between ground and stem, and the potential measurement region of stem could be identified by searching crossing points and ending points. The color coordinates of the potential measurement region were saved and corresponding point cloud data were generated based on the mapping relationship between color coordinate, depth coordinate and camera coordinate. Second, stem diameters were calculated by processing point cloud data. Noise points affected measurement accuracy of stem diameters, and K-nearest method was applied to remove scattered points from point cloud data. Then the filtered point cloud data of potential measurement region were clustered. There were some point cloud data on the edge of stem due to the measurement of time of flight (ToF), which were background noises. K-means method was used to divide the filtered point cloud data into 2 groups, and only the group whose central point was nearer to the camera was saved to represent maize stem. The saved point cloud data were one side of stem, and ellipse fitting based on least square method was carried out for the point cloud data. Long axis parameter and short axis parameter of ellipse were calculated respectively to indicate the stem diameters of maize. 20 samples were tested to verify aforementioned method, and the experimental results showed that the method proposed in this paper had a good performance in segmenting and identifying maize stem, though ellipse fitting method needed to be improved. The mean errors, standard deviation and mean relative errors of measuring stem diameters were 3.31 mm, 3.01 mm, 10.27% for long axis and 3.33 mm, 2.39 mm, 12.71% for short axis, respectively, indicating that the proposed method could be applicable for plant phenotyping. |
| Author | 仇瑞承 张漫 魏爽 李世超 李民赞 刘刚 |
| AuthorAffiliation | [1]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083;[2]农业部农业信息获取技术重点实验室,北京,100083 |
| AuthorAffiliation_xml | – name: 中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083%农业部农业信息获取技术重点实验室,北京,100083 |
| Author_FL | Liu Gang Zhang Man Li Shichao Li Minzan Wei Shuang Qiu Ruicheng |
| Author_FL_xml | – sequence: 1 fullname: Qiu Ruicheng – sequence: 2 fullname: Zhang Man – sequence: 3 fullname: Wei Shuang – sequence: 4 fullname: Li Shichao – sequence: 5 fullname: Li Minzan – sequence: 6 fullname: Liu Gang |
| Author_xml | – sequence: 1 fullname: 仇瑞承 张漫 魏爽 李世超 李民赞 刘刚 |
| BookMark | eNo9j8tKw0AYhWdRwVr7GOLGxPmTuf1LrVqFgiAFl2UyndQUnWqDaLsWRJS6UkEFn0GLoH0eTfQtjFRcHTh8nMscKbmes4QsAPUBUPLlrp-kqfOB0sATCtAPKEh_CD4NRImU__1ZUk3TJKIcQkkpgzJZ-nyafExGO_VVby1_eMseJ_n9WT66yJ_HX1ej_OUue738Pr_Obt-z8c08mYn1fmqrf1ohzY31Zm3Ta2zXt2orDc-oQHjANAaC2mICk4AagQnGrEVUqh1qbiHicWiQWypMxEMBoGMd8bY0TJpYhxWyOI090S7WrtPq9o77rihsuUHHnEa_54ZQXCtInJJmr-c6R0nBHvaTA90ftHbbUimUIAoRglOmGHKOlCFTnHIW_gCpaGaa |
| ClassificationCodes | S126%TP391.41 |
| ContentType | Journal Article |
| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| Copyright_xml | – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| DBID | 2RA 92L CQIGP ~WA 2B. 4A8 92I 93N PSX TCJ |
| DOI | 10.11975/j.issn.1002-6819.2017.z1.026 |
| DatabaseName | 维普_期刊 中文科技期刊数据库-CALIS站点 维普中文期刊数据库 中文科技期刊数据库- 镜像站点 Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Agriculture |
| DocumentTitleAlternate | Method for measurement of maize stem diameters based on RGB-D camera |
| DocumentTitle_FL | Method for measurement of maize stem diameters based on RGB-D camera |
| EndPage | 176 |
| ExternalDocumentID | nygcxb2017z1026 Wd788971678866504849559049485054 |
| GrantInformation_xml | – fundername: 北京市科技计划资助项目"作物精确化育种性状采集智能装备的研发与应用" funderid: (D151100004215002) |
| GroupedDBID | -04 2B. 2B~ 2RA 5XA 5XE 92G 92I 92L ABDBF ABJNI ACGFO ACGFS AEGXH AIAGR ALMA_UNASSIGNED_HOLDINGS CCEZO CHDYS CQIGP CW9 EOJEC FIJ IPNFZ OBODZ RIG TCJ TGD TUS U1G U5N ~WA 4A8 93N ACUHS PSX |
| ID | FETCH-LOGICAL-c826-14a9260e0174719a914644ee9988d3a5e1b5f3c95e06cb53611afab5d7c47cfa3 |
| ISSN | 1002-6819 |
| IngestDate | Thu May 29 04:08:34 EDT 2025 Wed Feb 14 10:02:34 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | z1 |
| Keywords | point cloud fitting 作物表型 stem diameter 测量 RGB-D相机 crops 点云拟合 农作物 plant phenotyping 茎粗 图像识别 RGB-D camera image recognition measurements |
| Language | Chinese |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c826-14a9260e0174719a914644ee9988d3a5e1b5f3c95e06cb53611afab5d7c47cfa3 |
| Notes | 11-2047/S Stem diameters of maize are important phenotype parameters and can characterize the crop growth and lodging resistance, drawing more attentions from breeders. Traditional measurement about stem diameters is usually manual measurement, which is timeconsuming, laborious, and subject to human error. In order to rapidly measure stem diameters of maize in field, a method based on RGB-D (red, green, blue - depth) camera was proposed in this paper to extract stem diameters of maize. The color images and depth images of the maize plants at the small bell stage were captured by a RGB-D camera in field. First, maize stem was extracted by processing the color image. It was hard to recognize maize just according to the color differences in red, green and blue component between maize and background due to the illumination variations. To solve the problem, the component that represented the difference between green signals and illumination brightness was calculated and applied to segment maize with Otsu algorithm, |
| PageCount | 7 |
| ParticipantIDs | wanfang_journals_nygcxb2017z1026 chongqing_primary_Wd788971678866504849559049485054 |
| PublicationCentury | 2000 |
| PublicationDate | 2017 |
| PublicationDateYYYYMMDD | 2017-01-01 |
| PublicationDate_xml | – year: 2017 text: 2017 |
| PublicationDecade | 2010 |
| PublicationTitle | 农业工程学报 |
| PublicationTitleAlternate | Transactions of the Chinese Society of Agricultural Engineering |
| PublicationTitle_FL | Transactions of the Chinese Society of Agricultural Engineering |
| PublicationYear | 2017 |
| Publisher | 中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083%农业部农业信息获取技术重点实验室,北京,100083 |
| Publisher_xml | – name: 中国农业大学现代精细农业系统集成研究教育部重点实验室,北京,100083%农业部农业信息获取技术重点实验室,北京,100083 |
| SSID | ssib051370041 ssib017478172 ssj0041925 ssib001101065 ssib023167668 |
| Score | 2.177294 |
| Snippet | 为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色图像和深度图像.... S126%TP391.41; 为实现田间玉米茎粗的快速测量,提出了一种基于RGB-D(RGB-Depth)相机的玉米茎粗参数提取方法.以小喇叭口期玉米为观测对象,利用RGB-D相机获取田间玉米的彩色... |
| SourceID | wanfang chongqing |
| SourceType | Aggregation Database Publisher |
| StartPage | 170 |
| SubjectTerms | 测量;图像识别;农作物;作物表型;RGB-D相机;茎粗;点云拟合 |
| Title | 基于RGB-D相机的玉米茎粗测量方法 |
| URI | http://lib.cqvip.com/qk/90712X/2017z1/Wd788971678866504849559049485054.html https://d.wanfangdata.com.cn/periodical/nygcxb2017z1026 |
| Volume | 33 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVEBS databaseName: EBSCOhost Academic Search Ultimate - TFS issn: 1002-6819 databaseCode: ABDBF dateStart: 20140101 customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn isFulltext: true dateEnd: 99991231 titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn omitProxy: true ssIdentifier: ssj0041925 providerName: EBSCOhost |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LbxMxELZCKiE4IJ5qeakH5hQ2xLvrtX1cJxsqJDigInqL9pmeUiitBDkjIQQKJ0ACJH4DVEjQH8AvgQT-BTPezUOo4tGL48zsfh57vPbYuzNm7EqRZDiNeKmTZYVy_FTiM5e7yklafpLnQZG61kns5q1g7Y5_Y0Ns1GpfF75a2t1JmunwQL-Sw2gVaahX8pL9D83OQJGAedQvpqhhTP9JxxAJ0F0wIUQ-pSq6fd04HYgkaANGQRSAbls-UpDvU0ZFoDRlDAfjQaRAtYlIFBe0pLuMAGUg0qDw-q7FQaK2LA_KAyunNi1JoWxBJIWigpBiJISCMENloQSEHQgDQlAhsqaatjcZKodk5KAje4kG021YnDaELVsuZkyDZEIgkgklU2A6DStdx9agLD-gOhkEEYs8RGhRAcTDZossOiJoNc2Ei1sgpa9nNV7TgB6oatStBvQyskbVcYf84IlCS2FnCoJpzmDoWz_ZHFIc198CdNsp_24mlaKgW_gToG3rK58i-JUxdtD4PcKWXNoXqrOl0HRMd26Yclp7z0ZOTqcW8LnHskvxCIL5wk9wj44dmH2sRK_qhX1vX8l5lMG0Ftf-VAeKGLK5NejfRzvIuqUNinjQX7Cg1k-yE9XSZzUs-_EpVhtunmbHw_52Ff4lP8Oufn-__21_ZHvx5O3n8bv9yZvHk9HTyYe9H89Hk4-vx5-e_XzyYvzqy3jv5Vm23o3W22tOdZ6Hk-Ii1uF-rHH1nNvacx1rnKR9P89xwa8yLxY5T0ThpVrkrSBNhBdwHhdxIjKZ-jItYu8cqw-2BvkyW5U6y_wYTV1XYdvzIFE8daVwU4n_cumtMHdW7d69MmxL72_KW2GrVfv0qmf8QW_wqJ8-TKhBh2iJB-cPg3uBHSOAct_uIqvvbO_ml9CS3UkuV93kF8frbs4 |
| linkProvider | EBSCOhost |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E5%9F%BA%E4%BA%8ERGB-D%E7%9B%B8%E6%9C%BA%E7%9A%84%E7%8E%89%E7%B1%B3%E8%8C%8E%E7%B2%97%E6%B5%8B%E9%87%8F%E6%96%B9%E6%B3%95&rft.jtitle=%E5%86%9C%E4%B8%9A%E5%B7%A5%E7%A8%8B%E5%AD%A6%E6%8A%A5&rft.au=%E4%BB%87%E7%91%9E%E6%89%BF+%E5%BC%A0%E6%BC%AB+%E9%AD%8F%E7%88%BD+%E6%9D%8E%E4%B8%96%E8%B6%85+%E6%9D%8E%E6%B0%91%E8%B5%9E+%E5%88%98%E5%88%9A&rft.date=2017&rft.issn=1002-6819&rft.volume=33&rft.issue=z1&rft_id=info:doi/10.11975%2Fj.issn.1002-6819.2017.z1.026&rft.externalDocID=Wd788971678866504849559049485054 |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fimage.cqvip.com%2Fvip1000%2Fqk%2F90712X%2F90712X.jpg http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fnygcxb%2Fnygcxb.jpg |