矮化密植枣园收获作业视觉导航路径提取
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摘要
针对矮化密植枣园环境的复杂性,提出一种基于图像处理的枣园导航基准线生成算法。选用B分量图进行处理,提出"行阈值分割"方法分割树干与背景;根据拍摄场景及视角提出"行间区域"方法剔除行间噪声;通过统计树干与地面交点位置分布区域选取图像五分之二向下区域进行处理;依据树干纵向灰度分布规律,采用浮动窗口灰度垂直投影方法结合形态学开闭运算提取树干区域;基于枣园行间线性分布特征引入"趋势线",而后利用点到直线的距离与设定阈值作比较选取树干与地面的交点;利用交点的位置分布将其归类,并采用最小二乘法原理拟合左右两侧边缘,提取边缘线上各行的几何中心点生成枣园导航基准线。通过对阴天、晴天、顺光、逆光、噪声多元叠加5种条件进行试验,结果表明,该算法具有一定的抗噪性能,单一工况条件导航基准线生成准确率可达83.4%以上,多工况条件准确率为45%。针对5种工况条件的视频检测,结果表明,单一工况条件算法动态检测准确率可达81.3%以上,每帧图像处理平均耗时低于1.7 s,多工况条件检测准确率为42.3%,每帧图像平均耗时1.0 s。该研究可为矮化密植果园实现机器人自主导航作业提供参考。
An algorithm based on image processing technology was proposed for generating navigation directrix in complex circumstance of short-stalked and close-planting jujube orchard.The hatching method was used to analyze the distribution of target pixels and then proper processing image was obtained.Tree trunk and background were segmented based on B component of image which was binarized by threshold of each scan line.By analyzing the distribution of crossing points between tree truck and ground,the chief processing section,or the region of interest(ROI),was defined and chosen from two-fifths of image area below.Then in the light of trunk longitudinal gray scale distribution,tree trunks location was extracted with gray scale vertical projection method and morphology principle by setting a superficial window to dynamically scan ROI.In order to describe line trend in short-stalked and close-planting jujube orchard,trend lines were introduced,which included the right one and the left one in terms of ridge and furrow.To describe linear distribution trait of ridge and furrow,crossing points between tree and ground were obtained by comparing the shortest distance of candidate point to its corresponding trend line with a man-made threshold value.Afterwards,those selected points were classified separately into 2clusters in terms of their distribution region which was located at right or left part of image longitudinal symmetry axis,with the point set available to fit the border line of ridge separately.The least square method was used for detecting the right and left border lines,and navigation directrix was generated by extracting the center points between 2 border lines.The method of extracting navigation path was searched by analyzing the condition of short-stalked and close-planting jujube orchard under harvesting operation,and the accuracy and reliability of the algorithm were analyzed and evaluated under a variety of environmental conditions.The study of the algorithm was still in the simulation stage and the specific navigation effect of the algorithm was related to the actual navigation operations,so algorithm performance could not fully represent the actual navigation applications.In order to measure the algorithm reliability and real-time parameters,5 different scene conditions,which included 4 single factor working conditions and one multiple factor working condition,were tested.The experimental results showed that the algorithm could generate navigation directrix accurately and showed a good noise robustness.Under 4single factor working conditions,the accuracy was more than 81.3%,and the average processing time consumed was less than11.9 s to each frame image;by video detection,the accuracy was more than 83.4%,and the average processing time consumed was less than 1.7 s to each frame image.Under multiple factor working condition,the accuracy only reached 45%and the average processing time consumed was 9.4 s;by video detection,the accuracy only reached 42.3%and the average processing time consumed was 1.0 s.Therefore,for subsequent tasks,work should be done to improve the real time performance and practicality of the algorithm for various surroundings,so as to enhance the sensitivity of the algorithm under the multi-mode condition.The novelty of this paper is to propose several new methods to solve practical problems.The research provides a reference for autonomous navigation of robot in short-stalked and close-planting jujube orchard.
An algorithm based on image processing technology was proposed for generating navigation directrix in complex circumstance of short-stalked and close-planting jujube orchard.The hatching method was used to analyze the distribution of target pixels and then proper processing image was obtained.Tree trunk and background were segmented based on B component of image which was binarized by threshold of each scan line.By analyzing the distribution of crossing points between tree truck and ground,the chief processing section,or the region of interest(ROI),was defined and chosen from two-fifths of image area below.Then in the light of trunk longitudinal gray scale distribution,tree trunks location was extracted with gray scale vertical projection method and morphology principle by setting a superficial window to dynamically scan ROI.In order to describe line trend in short-stalked and close-planting jujube orchard,trend lines were introduced,which included the right one and the left one in terms of ridge and furrow.To describe linear distribution trait of ridge and furrow,crossing points between tree and ground were obtained by comparing the shortest distance of candidate point to its corresponding trend line with a man-made threshold value.Afterwards,those selected points were classified separately into 2clusters in terms of their distribution region which was located at right or left part of image longitudinal symmetry axis,with the point set available to fit the border line of ridge separately.The least square method was used for detecting the right and left border lines,and navigation directrix was generated by extracting the center points between 2 border lines.The method of extracting navigation path was searched by analyzing the condition of short-stalked and close-planting jujube orchard under harvesting operation,and the accuracy and reliability of the algorithm were analyzed and evaluated under a variety of environmental conditions.The study of the algorithm was still in the simulation stage and the specific navigation effect of the algorithm was related to the actual navigation operations,so algorithm performance could not fully represent the actual navigation applications.In order to measure the algorithm reliability and real-time parameters,5 different scene conditions,which included 4 single factor working conditions and one multiple factor working condition,were tested.The experimental results showed that the algorithm could generate navigation directrix accurately and showed a good noise robustness.Under 4single factor working conditions,the accuracy was more than 81.3%,and the average processing time consumed was less than11.9 s to each frame image;by video detection,the accuracy was more than 83.4%,and the average processing time consumed was less than 1.7 s to each frame image.Under multiple factor working condition,the accuracy only reached 45%and the average processing time consumed was 9.4 s;by video detection,the accuracy only reached 42.3%and the average processing time consumed was 1.0 s.Therefore,for subsequent tasks,work should be done to improve the real time performance and practicality of the algorithm for various surroundings,so as to enhance the sensitivity of the algorithm under the multi-mode condition.The novelty of this paper is to propose several new methods to solve practical problems.The research provides a reference for autonomous navigation of robot in short-stalked and close-planting jujube orchard.
引文
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[3]吴佳艺,杨庆华,鲍官军,等.基于机器视觉的林间导航路径生成算法[J].农业机械学报,2009,40(7):176-179.Wu Jiayi,Yang Qinghua,Bao Guanjun,et al.Algorithm of path navigation line for robot in forestry environment based on machine vision[J].Transactions of the CSAM,2009,40(7):176-179.(in Chinese with English abstract)
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[7]Frits K V E,Gerie W A M H,Lambertus A P L,et al.A mobile field robot with vision-based detection of volunteer potato plants in a corn crop[J].Weed Technology,2006,20(4):853-861.
[8]Patrick F,Tobias F,Karsten B.Detection of field structures for agricultural vehicle guidance[J].Kiinstl Intell,2013,27:351-357.
[9]Griepentrog H W,Duhring Jaeger C L,Paraforos D S.Robots for field operations with comprehensive multilayer control[J].Kiinstl Intell,2013,27:325-333.
[10]Liu Bin,Liu Gang,Wu Xue.Resarch on machine vison based agricultural automatic guidance system[J].Computer and Computing Technologies in Agriculture,2008,1:659-666.
[11]Gokhan B.Long distance autonomous trajectory tracking for an orchard vehicle[J].Industrial Robot,2013,40(1):27-40.
[12]Zhang Tian,Xia Junfang,Wu Gang,et al.Automatic navigation path detection method for tillage machines working on high crop stubble fields based on machine vision[J].Int J Agric&Biol Eng,2014,7(4):29-37.
[13]Xue Jinlin,Zhang Lei,Grift T E.Variable field-of-view machine vision based row guidance of an agricultural robot[J].Computers and Electronics in Agriculture,2012,84:85-91.
[14]Rovira-Ma's F,Zhang Q,Reid J F,et al.Hough-transformbased vision algorithm for crop row detection of an automated agricultural vehicle[J].Automobile Engineering,2005,219:999-1010.
[15]Keun H C,Sang K H,Sang H H,et al.Morphology-based guidance line extraction for an autonomous weeding robot in paddy fields[J].Computers and Electronics in Agriculture,2015,113:266-274.
[16]Jiang Haibo,Xiao Yilong,Zhang Yunwei,et al.Curve path detection of unstructured roads for the outdoor robot navigation[J].Mathematical and Computer Modelling,2013,58:536-544..
[17]Eiji M,Masahiko S,Mikio U.Vision-based navigation system for autonomous transportation vehicle[J].Precision Agriculture,2005,6:239-254.
[18]Li Nan,Zhang Chunlong,Chen Ziwen,et al.Crop positioning for robotic intra-row weeding based on machine vision[J].Journal of International Agriculture and Bioengineering,2015,8(6):20-29.
[19]Sturzl W,Grixa I,Mair E,et al.Three-dimensional models of natural environments and the mapping of navigational information[J].Journal of Comparative Physiology A,2015,201:563-584.
[20]Liu Yang,Chen Bingqi,Detection for weak navigation line for wheat planter based on machine vision[J].Applied Mechanics and Materials,2013(246/247):235-240.
[21]李景彬,陈兵旗,刘阳,等.采棉机视觉导航路线图像检测方法[J].农业工程学报,2013,29(11):11-19.Li Jingbin,Chen Bingqi,Liu Yang,et al.Detection for navigation route for cotton harvester based on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(11):11-19.(in Chinese with English abstract)
[22]张铁民,庄晓霖.基于DM642的高地隙小车的田间路径识别导航系统[J].农业工程学报,2015,31(4):160-167.Zhang Tiemin,Zhuang Xiaolin.Identification and navigation system of farmland path for high-clearance vehicle based on DM642[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(4):160-167.(in Chinese with English abstract)
[23]冯娟,刘刚,司永胜,等.果园视觉导航基准线生成算法[J].农业机械学报,2012,43(7):185-189,184.Feng Juan,Liu Gang,Si Yongsheng,et al.Algorithm based on image processing technology to generate navigation directrix in orchard[J].Transactions of the CSAM,2012,43(7):185-189,184.(in Chinese with English abstract)
[24]He Bei,Liu Gang,Ji Ying,et al.Auto recognition of navigation path for harvest robot based on machine vision[J].Springer Berlin Heidelberg,2011,344:138-148.
[25]王娅利,王青.绥德县枣树矮化密植栽培技术[J].现代农业技术,2015(10):83-84.
[26]冯国涛.万泉北川苹果优质高效示范园生产经验[J].山西果树,2012(2):24-25.
[27]漆联全.新疆红枣产业的现状、要求及其发展趋势[J].新疆农业科学,2010(增刊2):8-12.Qi Lianquan.The present situation,requirements and development trends of Xinjiang red date industry[J].Xinjiang Agricultural Science,2010(Supp.2):8-12.(in Chinese with English abstract)
[28]赵晓艳.枣树种植及田间管理机械化技术应用效果[J].农机使用与维修,2016,3:66-67.Zhao Xiaoyan.Jujube tree planting and effect of field management mechanization technology application[J].Use and Maintenance of Agricultural Machinery,2016,3:66-67.(in Chinese with English abstract)
[29]何洁,孟庆宽,张漫,等.基于边缘检测与扫描滤波的农机导航基准线提取方法[J].农业机械学报,2014,45(增刊1):265-270.He Jie,Meng Qingkuan,Zhang Man,et al.Crop baseline extraction method for off-road vehicle based on boundary detection and scan-filter[J].Transactions of the Chinese Society of Agricultural Machinery,2014,45(Supp.l):265-270.(in Chinese with English abstract)
[30]王新忠,韩旭,毛罕平,等.基于最小二乘法的温室番茄垄间视觉导航路径检测[J].农业机械学报,2012,43(6):161-166.Wang Xinzhong,Han Xu,Mao Hanping,et al.Navigation line detection of tomato ridges in greenhouse based on least square method[J].Transactions of the Chinese Society of Agricultural Machinery,2012,43(6):161-166.(in Chinese with English abstract)
[31]杨庆华,吴佳艺,鲍官军,等.农林环境机器视觉导航路径生成算法及应用[J].农业机械学报,2009,40(3):147-151.Yang Qinghua,Wu Jiayi,Bao Guanjun.Algorithms of path guidance line based on computer vision and their applications in agriculture and forestry environment[J].Transactions of the Chinese Society of Agricultural Machinery,2009,40(3):147-151.(in Chinese with English abstract)
[32]赵颖,孙群,陈兵旗,等.基于机器视觉的非结构化道路导航路径检测方法[J].农业机械学报,2007,38(6):202-204.Zhao Ying,Sun Qun,Chen Bingqi,et al.Fast detection of furrows based on machine vision on autonomous mobile robot[J].Transactions of the Chinese Society for Agricultural Machinery,2007,38(6):202-204.(in Chinese with English abstract)
[33]冯娟,刘刚,司永胜,等.果园视觉导航基准线生成算法[J].农业机械学报,2012,43(7):185-189,184.Fen Juan,Liu Gang,Si Yongsheng,et al.Algorithm based on image processing technology to generate navigation directrix in orchard[J].Transactions of the Chinese Society for Agricultural Machinery,2012,43(7):185-189,184.(in Chinese with English abstract)
[2]李景彬,陈兵旗,刘阳.棉花铺膜播种机导航路线图像检测方法[J].农业机械学报,2014,45(1):40-45.Li Jingbin,Chen Bingqi,Liu Yang.Image detection method of navigation route of cotton plastic filmmulch planter[J].Transactions of the CSAM,2014,45(1):40-45.(in Chinese with English abstract)
[3]吴佳艺,杨庆华,鲍官军,等.基于机器视觉的林间导航路径生成算法[J].农业机械学报,2009,40(7):176-179.Wu Jiayi,Yang Qinghua,Bao Guanjun,et al.Algorithm of path navigation line for robot in forestry environment based on machine vision[J].Transactions of the CSAM,2009,40(7):176-179.(in Chinese with English abstract)
[4]Barawid J,Oscar C M,et al.Development of an autonomous navigation system using a two-dimensional laser scanner in an orchard application[J].Biosystems Engineering,2007,96:139-149.
[5]Pawin T,Tofael A,Tomohiro T.Navigation of autonomous tractor for orchards and plantations using a laser range finder:Automatic control of trailer position with tractor[J].Biosystems Engineering,2016,147:90-103.
[6]Benson E R,Reid J F,Zhang Q.Machine vision-based guidance system for agricultural grain harvesters using cut-edge detection[J].Biosystems Engineering,2003,86(4):389-398.
[7]Frits K V E,Gerie W A M H,Lambertus A P L,et al.A mobile field robot with vision-based detection of volunteer potato plants in a corn crop[J].Weed Technology,2006,20(4):853-861.
[8]Patrick F,Tobias F,Karsten B.Detection of field structures for agricultural vehicle guidance[J].Kiinstl Intell,2013,27:351-357.
[9]Griepentrog H W,Duhring Jaeger C L,Paraforos D S.Robots for field operations with comprehensive multilayer control[J].Kiinstl Intell,2013,27:325-333.
[10]Liu Bin,Liu Gang,Wu Xue.Resarch on machine vison based agricultural automatic guidance system[J].Computer and Computing Technologies in Agriculture,2008,1:659-666.
[11]Gokhan B.Long distance autonomous trajectory tracking for an orchard vehicle[J].Industrial Robot,2013,40(1):27-40.
[12]Zhang Tian,Xia Junfang,Wu Gang,et al.Automatic navigation path detection method for tillage machines working on high crop stubble fields based on machine vision[J].Int J Agric&Biol Eng,2014,7(4):29-37.
[13]Xue Jinlin,Zhang Lei,Grift T E.Variable field-of-view machine vision based row guidance of an agricultural robot[J].Computers and Electronics in Agriculture,2012,84:85-91.
[14]Rovira-Ma's F,Zhang Q,Reid J F,et al.Hough-transformbased vision algorithm for crop row detection of an automated agricultural vehicle[J].Automobile Engineering,2005,219:999-1010.
[15]Keun H C,Sang K H,Sang H H,et al.Morphology-based guidance line extraction for an autonomous weeding robot in paddy fields[J].Computers and Electronics in Agriculture,2015,113:266-274.
[16]Jiang Haibo,Xiao Yilong,Zhang Yunwei,et al.Curve path detection of unstructured roads for the outdoor robot navigation[J].Mathematical and Computer Modelling,2013,58:536-544..
[17]Eiji M,Masahiko S,Mikio U.Vision-based navigation system for autonomous transportation vehicle[J].Precision Agriculture,2005,6:239-254.
[18]Li Nan,Zhang Chunlong,Chen Ziwen,et al.Crop positioning for robotic intra-row weeding based on machine vision[J].Journal of International Agriculture and Bioengineering,2015,8(6):20-29.
[19]Sturzl W,Grixa I,Mair E,et al.Three-dimensional models of natural environments and the mapping of navigational information[J].Journal of Comparative Physiology A,2015,201:563-584.
[20]Liu Yang,Chen Bingqi,Detection for weak navigation line for wheat planter based on machine vision[J].Applied Mechanics and Materials,2013(246/247):235-240.
[21]李景彬,陈兵旗,刘阳,等.采棉机视觉导航路线图像检测方法[J].农业工程学报,2013,29(11):11-19.Li Jingbin,Chen Bingqi,Liu Yang,et al.Detection for navigation route for cotton harvester based on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(11):11-19.(in Chinese with English abstract)
[22]张铁民,庄晓霖.基于DM642的高地隙小车的田间路径识别导航系统[J].农业工程学报,2015,31(4):160-167.Zhang Tiemin,Zhuang Xiaolin.Identification and navigation system of farmland path for high-clearance vehicle based on DM642[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(4):160-167.(in Chinese with English abstract)
[23]冯娟,刘刚,司永胜,等.果园视觉导航基准线生成算法[J].农业机械学报,2012,43(7):185-189,184.Feng Juan,Liu Gang,Si Yongsheng,et al.Algorithm based on image processing technology to generate navigation directrix in orchard[J].Transactions of the CSAM,2012,43(7):185-189,184.(in Chinese with English abstract)
[24]He Bei,Liu Gang,Ji Ying,et al.Auto recognition of navigation path for harvest robot based on machine vision[J].Springer Berlin Heidelberg,2011,344:138-148.
[25]王娅利,王青.绥德县枣树矮化密植栽培技术[J].现代农业技术,2015(10):83-84.
[26]冯国涛.万泉北川苹果优质高效示范园生产经验[J].山西果树,2012(2):24-25.
[27]漆联全.新疆红枣产业的现状、要求及其发展趋势[J].新疆农业科学,2010(增刊2):8-12.Qi Lianquan.The present situation,requirements and development trends of Xinjiang red date industry[J].Xinjiang Agricultural Science,2010(Supp.2):8-12.(in Chinese with English abstract)
[28]赵晓艳.枣树种植及田间管理机械化技术应用效果[J].农机使用与维修,2016,3:66-67.Zhao Xiaoyan.Jujube tree planting and effect of field management mechanization technology application[J].Use and Maintenance of Agricultural Machinery,2016,3:66-67.(in Chinese with English abstract)
[29]何洁,孟庆宽,张漫,等.基于边缘检测与扫描滤波的农机导航基准线提取方法[J].农业机械学报,2014,45(增刊1):265-270.He Jie,Meng Qingkuan,Zhang Man,et al.Crop baseline extraction method for off-road vehicle based on boundary detection and scan-filter[J].Transactions of the Chinese Society of Agricultural Machinery,2014,45(Supp.l):265-270.(in Chinese with English abstract)
[30]王新忠,韩旭,毛罕平,等.基于最小二乘法的温室番茄垄间视觉导航路径检测[J].农业机械学报,2012,43(6):161-166.Wang Xinzhong,Han Xu,Mao Hanping,et al.Navigation line detection of tomato ridges in greenhouse based on least square method[J].Transactions of the Chinese Society of Agricultural Machinery,2012,43(6):161-166.(in Chinese with English abstract)
[31]杨庆华,吴佳艺,鲍官军,等.农林环境机器视觉导航路径生成算法及应用[J].农业机械学报,2009,40(3):147-151.Yang Qinghua,Wu Jiayi,Bao Guanjun.Algorithms of path guidance line based on computer vision and their applications in agriculture and forestry environment[J].Transactions of the Chinese Society of Agricultural Machinery,2009,40(3):147-151.(in Chinese with English abstract)
[32]赵颖,孙群,陈兵旗,等.基于机器视觉的非结构化道路导航路径检测方法[J].农业机械学报,2007,38(6):202-204.Zhao Ying,Sun Qun,Chen Bingqi,et al.Fast detection of furrows based on machine vision on autonomous mobile robot[J].Transactions of the Chinese Society for Agricultural Machinery,2007,38(6):202-204.(in Chinese with English abstract)
[33]冯娟,刘刚,司永胜,等.果园视觉导航基准线生成算法[J].农业机械学报,2012,43(7):185-189,184.Fen Juan,Liu Gang,Si Yongsheng,et al.Algorithm based on image processing technology to generate navigation directrix in orchard[J].Transactions of the Chinese Society for Agricultural Machinery,2012,43(7):185-189,184.(in Chinese with English abstract)