基于机器视觉的株间机械除草装置的作物识别与定位方法
株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了一种株间机械除草装置的作物识别与定位方法.利用2G-R-B方法将作物RGB彩色图像进行灰度化,再选用Ostu法二值化、连续腐蚀和连续膨胀等方法对图像进行了初步处理.根据行像素累加曲线和曲线的标准偏差扫描线获得作物行区域信息,以作物行区域为处理对象,利用列像素累加曲线、曲线标准偏差和正弦波曲线拟合识别出作物,并结合二值图像中绿色植物连通域的质心获得作物位置信息.试验结果表明,该方法可以正确识别出作物并提供准确的定位信息,能适应不同天气状况、不同种类的...
Saved in:
| Published in | 农业工程学报 Vol. 29; no. 10; pp. 12 - 18 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州 510642%华南农业大学工程学院,广州 510642
2013
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.3969/j.issn.1002-6819.2013.10.002 |
Cover
| Abstract | 株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了一种株间机械除草装置的作物识别与定位方法.利用2G-R-B方法将作物RGB彩色图像进行灰度化,再选用Ostu法二值化、连续腐蚀和连续膨胀等方法对图像进行了初步处理.根据行像素累加曲线和曲线的标准偏差扫描线获得作物行区域信息,以作物行区域为处理对象,利用列像素累加曲线、曲线标准偏差和正弦波曲线拟合识别出作物,并结合二值图像中绿色植物连通域的质心获得作物位置信息.试验结果表明,该方法可以正确识别出作物并提供准确的定位信息,能适应不同天气状况、不同种类的作物,棉苗正确识别率为95.8%,生菜苗正确识别率为100%,该方法为株间机械除草装置避苗和除草自动控制提供了基本条件. |
|---|---|
| AbstractList | TP2%S224.1+5; 株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了一种株间机械除草装置的作物识别与定位方法.利用2G-R-B方法将作物RGB彩色图像进行灰度化,再选用Ostu法二值化、连续腐蚀和连续膨胀等方法对图像进行了初步处理.根据行像素累加曲线和曲线的标准偏差扫描线获得作物行区域信息,以作物行区域为处理对象,利用列像素累加曲线、曲线标准偏差和正弦波曲线拟合识别出作物,并结合二值图像中绿色植物连通域的质心获得作物位置信息.试验结果表明,该方法可以正确识别出作物并提供准确的定位信息,能适应不同天气状况、不同种类的作物,棉苗正确识别率为95.8%,生菜苗正确识别率为100%,该方法为株间机械除草装置避苗和除草自动控制提供了基本条件. 株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了一种株间机械除草装置的作物识别与定位方法.利用2G-R-B方法将作物RGB彩色图像进行灰度化,再选用Ostu法二值化、连续腐蚀和连续膨胀等方法对图像进行了初步处理.根据行像素累加曲线和曲线的标准偏差扫描线获得作物行区域信息,以作物行区域为处理对象,利用列像素累加曲线、曲线标准偏差和正弦波曲线拟合识别出作物,并结合二值图像中绿色植物连通域的质心获得作物位置信息.试验结果表明,该方法可以正确识别出作物并提供准确的定位信息,能适应不同天气状况、不同种类的作物,棉苗正确识别率为95.8%,生菜苗正确识别率为100%,该方法为株间机械除草装置避苗和除草自动控制提供了基本条件. |
| Abstract_FL | Intra-row mechanical weeding, as a non-chemical weed control technology, reduces the application of chemical herbicides and is beneficial to the environment protection and sustainable development for agriculture as well. Most crops are cultivated in rows with a defined sowing or transplanting pattern, i.e. with a constant spacing distance. This is an important feature that can be used for plant recognition and localization. The goal of this study presented herein is to propose a recognition and localization approach, taking advantage of the knowledge of the sowing or transplanting pattern, to avoid crop automatically and enter into the intra-row area for intelligent intra-row mechanical weeding device. The RGB imaged plants were distinguished from soil by analyzing the excessive green (2G-R-B) vegetation index image. The Ostu algorithm method was employed to transform a gray image to a binary image. And then the binary image was dilated and eroded three times repeatedly to remove isolated pixels in binary images or to remove noise for subsequent analysis. The standard deviation of longitudinal histogram was used as the scanning line to get the crop row area information in a binary image. The next step was to sum up all pixels of the crop row area per column, thus forming a signal with a frequency that corresponds to the average crop distance. The target regions and center points were obtained by analyzing the lateral histogram with the horizontal scan line. The most probable crop regions were filtered from all the target regions using a sinusoid which was fitted lateral histogram based on the distance between crops. The phasing of the sinusoid was given by least square fit for all the center points. After fusing the center of crop row and the centroid of green plants in binary image, the plants localization were obtained through searching the closest fusion result to the sinusoid peeks. Test results showed that, the method was sufficient in plants recognition and localization for intra-row mechanical weeding under different weather and field conditions. The accurate identification rate was 95.8%with the absolute error of 4.2 pixels in the x-direction and 1.4 pixels in the y-direction for cotton seedlings. An identification rate of 100% with the absolute error of 6.8 pixels in the x-direction and 15.3 pixels in the y-direction was achieved for lettuce seedlings. The position of the crop was correctly determined for 100%of all the images. The positioning error for lettuce and cotton seedlings was 17.6 pixels and 5.0 pixels, respectively. Main factors that influence the performance of the recognition and localization are weed pressure and the plant growth conditions. This study provides the basics for mechanical weed control devices to seedling avoidance and automatic weed control. |
| Author | 胡炼 罗锡文 曾山 张智刚 陈雄飞 林潮兴 |
| AuthorAffiliation | 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642 华南农业大学工程学院,广州510642 |
| AuthorAffiliation_xml | – name: 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州 510642%华南农业大学工程学院,广州 510642 |
| Author_xml | – sequence: 1 fullname: 胡炼 罗锡文 曾山 张智刚 陈雄飞 林潮兴 |
| BookMark | eNo9j8tKw0AUhmdRwap9CEFwlTiTuSSzlOINC266L5NpUlN0qg2i3Wuxi3an0lJQVKgXqIIutNC3SdL0LRypuDqc7_84h38BZFRNeQCsIGhizvha1QzCUJkIQstgDuKmBRHWq6lBBmT_-TzIhWHgQoqwDSFBWbAb346iUSfpj-LuUzpopoPWpHee3L1Mbz41TO7fp93HtN1KHy4m46GOonF_0npO35rx5Wv01YmHvWjcTq6_k4-rJTDni4PQy_3NRVDc3Cjmt43C3tZOfr1gSOoQw7e5TW3IygKVLYaEj22KkIDYYQ7G0pfEo8R1CLc4dCxmu2XpSYEEowJS10J4EazOzp4K5QtVKVVrJ3WlH5ZUoyLP3N_uujEk2lyemXK_pirHgXaP6sGhqDdKhHLEObHxD4fWeK4 |
| ClassificationCodes | TP2%S224.1+5 |
| 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 W95 ~WA 2B. 4A8 92I 93N PSX TCJ |
| DOI | 10.3969/j.issn.1002-6819.2013.10.002 |
| DatabaseName | 维普期刊资源整合服务平台 中文科技期刊数据库-CALIS站点 中文科技期刊数据库-7.0平台 中文科技期刊数据库-农业科学 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 | Plant recognition and localization for intra-row mechanical weeding device based on machine vision |
| DocumentTitle_FL | Plant recognition and localization for intra-row mechanical weeding device based on machine vision |
| EndPage | 18 |
| ExternalDocumentID | nygcxb201310004 45919947 |
| 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 W95 ~WA 4A8 93N ACUHS PSX |
| ID | FETCH-LOGICAL-c584-f7975706da1d261af37511a0386833cfc4e54b8492908267bdceca1a65a05b213 |
| ISSN | 1002-6819 |
| IngestDate | Thu May 29 04:04:17 EDT 2025 Wed Feb 14 10:43:10 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 10 |
| Keywords | agricultural machinery intra-row mechanical weed control 机器视觉 作物识别 株间机械除草 除草 定位 crop recognition weed control location 农业机械 machine vision |
| Language | Chinese |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c584-f7975706da1d261af37511a0386833cfc4e54b8492908267bdceca1a65a05b213 |
| Notes | Hu Lian 1,2 , Luo Xiwen 1,2 , Zeng Shan 1,2 , Zhang Zhigang 1,2 , Chen Xiongfei 1,2 , Lin Chaoxing 1,2 （1. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 2. College of Engineering, South China Agricultural University, Guangzhou 510642, China） 11-2047/S Intra-row mechanical weeding, as a non-chemical weed control technology, reduces the application of chemical herbicides and is beneficial to the environment protection and sustainable development for agriculture as well. Most crops are cultivated in rows with a defined sowing or transplanting pattern, i.e. with a constant spacing distance. This is an important feature that can be used for plant recognition and localization. The goal of this study presented herein is to propose a recognition and localization approach, taking advantage of the knowledge of the sowing or transplanting pattern, to avoid crop automatically and enter into the intra-row area for |
| PageCount | 7 |
| ParticipantIDs | wanfang_journals_nygcxb201310004 chongqing_primary_45919947 |
| PublicationCentury | 2000 |
| PublicationDate | 2013 |
| PublicationDateYYYYMMDD | 2013-01-01 |
| PublicationDate_xml | – year: 2013 text: 2013 |
| 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 | 2013 |
| Publisher | 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州 510642%华南农业大学工程学院,广州 510642 |
| Publisher_xml | – name: 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州 510642%华南农业大学工程学院,广州 510642 |
| SSID | ssib051370041 ssib017478172 ssj0041925 ssib001101065 ssib023167668 |
| Score | 2.016349 |
| Snippet | 株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了一种株间机械除... TP2%S224.1+5; 株间机械除草技术可进一步减少化学除草剂的使用,有利于环境保护和农业可持续发展.为实现智能化的株间机械除草装置自主避让作物并进入株间区域,该研究提出了... |
| SourceID | wanfang chongqing |
| SourceType | Aggregation Database Publisher |
| StartPage | 12 |
| SubjectTerms | 作物识别 农业机械 定位 机器视觉 株间机械除草 除草 |
| Title | 基于机器视觉的株间机械除草装置的作物识别与定位方法 |
| URI | http://lib.cqvip.com/qk/90712X/201310/45919947.html https://d.wanfangdata.com.cn/periodical/nygcxb201310004 |
| Volume | 29 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVALS databaseName: IngentaConnect Open Access Journals issn: 1002-6819 databaseCode: FIJ dateStart: 20090101 customDbUrl: isFulltext: true dateEnd: 20151231 titleUrlDefault: http://www.ingentaconnect.com/content/title?j_type=online&j_startat=Aa&j_endat=Af&j_pagesize=200&j_page=1 omitProxy: true ssIdentifier: ssj0041925 providerName: Ingenta |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3LThRBcIKYGD0YnxF8hAN9MouzMz093ceZZTaI0RMm3Dbz2FlOiyIkylmJHOCmBkLUqAk-EjTRg5LwN7vL8hdW1fTOTgBRSTaTTlV1dT063VWz1T2GMWonpkhSHpZsOzJLXKZxSSVY6wrOFzKJREInvO_eExP3-eS0Mz0w-LpQtbQwH43Fi4eeKzmOVwEGfsVTsv_h2ZwpAKAN_oUneBie_-RjFjhMVZnvsYDjUwYsEExVCAIoxTzJAsk8l0nRaygWuEwBMUdiz2QeECumXObzQndAWcw3CQV8OHaX49Qd-NhMOsjHH2deUGDIEQIcAhrIy4irNLrDJLR9opEkqoN9lad7AXMcXTBfYcO3WfZdzF7oTBxIvIyDIh19l3kkCWgqfeIJIgnkID1A9SYUiW8zr0yigWaVPobUAP1RVU4kJEd_iyaAz3yS2S_Dr48BQAWtiCRKG16idMX3KdlBWJr7hB_X-sts3MMUA4t7bkGfnDi30cFeB52X2zr3GXGW2aAOWllrHWiTSVPzAbdhg6YRGg8YWkiMVpTUcMlnmTlVz50BomBKyYqGwHAWtYHGr2qfqeAmLNOQlTLLOb5F_uj8bM5aRw1c2I1xuxZS76l6ITIL262uwM8Ct2wf3x8S2EooCgmQ41jOEYs67TGq67T6oVBeoNp80ogfR0iD_3_xE8ZJy4VIFq-RvT3ZTzfK-EYl3w8tvFVC9NN3p2zjxyPykjMsuHCo-kILccoY1RLeOko-vPZlZrbZeAjBLJ0tbKZhs1EIg6fOGWd1_jriZYvReWNgceaCccZrzOk7fOoXjTvtN9ut7dXOxnZ77WN3c6m7uby7_rTz9vPeqx8A7Lz7trf2obuy3H3_bHdnC1CtnY3d5U_dr0vt519aP1fbW-utnZXOy1-d7y8uGVPVYKoyUdLfbCnFkMqUUle5jgvLf1hOLFEOU9uFjC40bSmkbcdpzOsOjySHpAxyD-FGSVyPw3IonNB0IqtsXzYGm7PN-hVjREGnJKzLkKcR58oMkzBRVpRGEjIoN0mGjOHcKrUH2dU8Ne4ovOzcHTJGtJlqer1-VNvn0-G_k1w1Tlv09Rt843rNGJyfW6hfhxxkPrpBE-E3GPTgXw |
| linkProvider | Ingenta |
| 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%8E%E6%9C%BA%E5%99%A8%E8%A7%86%E8%A7%89%E7%9A%84%E6%A0%AA%E9%97%B4%E6%9C%BA%E6%A2%B0%E9%99%A4%E8%8D%89%E8%A3%85%E7%BD%AE%E7%9A%84%E4%BD%9C%E7%89%A9%E8%AF%86%E5%88%AB%E4%B8%8E%E5%AE%9A%E4%BD%8D%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=%E8%83%A1%E7%82%BC&rft.au=%E7%BD%97%E9%94%A1%E6%96%87&rft.au=%E6%9B%BE%E5%B1%B1&rft.au=%E5%BC%A0%E6%99%BA%E5%88%9A&rft.date=2013&rft.pub=%E5%8D%8E%E5%8D%97%E5%86%9C%E4%B8%9A%E5%A4%A7%E5%AD%A6%E5%8D%97%E6%96%B9%E5%86%9C%E4%B8%9A%E6%9C%BA%E6%A2%B0%E4%B8%8E%E8%A3%85%E5%A4%87%E5%85%B3%E9%94%AE%E6%8A%80%E6%9C%AF%E6%95%99%E8%82%B2%E9%83%A8%E9%87%8D%E7%82%B9%E5%AE%9E%E9%AA%8C%E5%AE%A4%2C%E5%B9%BF%E5%B7%9E+510642%25%E5%8D%8E%E5%8D%97%E5%86%9C%E4%B8%9A%E5%A4%A7%E5%AD%A6%E5%B7%A5%E7%A8%8B%E5%AD%A6%E9%99%A2%2C%E5%B9%BF%E5%B7%9E+510642&rft.issn=1002-6819&rft.issue=10&rft.spage=12&rft.epage=18&rft_id=info:doi/10.3969%2Fj.issn.1002-6819.2013.10.002&rft.externalDocID=nygcxb201310004 |
| 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 |