质心跟踪视频棉花行数动态计数方法
|
摘要
为了实现无人植保车在棉田全覆盖视觉导航,该文提出了一种基于视频的棉花行动态计数方法,将棉花行数作为植保车直线植保作业行驶到田端后,判断2个直线作业区间隔距离的依据,以适应实际作业环境中不同的棉花种植行距。通过2G-R-B将彩色图像转化为灰度图像,强调了棉花行信息;通过在坐标系中设置固定位置和大小的关注区域,在减小计算量的同时,有效避免了田端缺苗、棉花行不规则等现象对检测结果造成的影响;通过对关注区域内各列灰度累计曲线的波峰筛选,适应3个生长期的棉花行的定位,识别正确率高于85%;通过设置浮动窗口并求其灰度质心为跟踪目标,提高了不同生长期和不同农田环境下的目标识别和跟踪适应性;通过对质心构建目标窗口,并计算前后帧目标窗口在图像坐标系中所在位置的重叠率,将后一帧目标窗口遍历前一帧图像中的目标窗口,关联重叠率>0.1的目标窗口,实现了视频图像中多个棉花行的跟踪。结果表明:该算法对于不同生长期的棉花行有较好的跟踪效果,对田端缺苗、杂草等农田环境有较好的鲁棒性。每帧图像的平均处理时间为150 ms,能够满足实时处理要求。
Pesticide spraying is one of the most important farm activities related to the protection of plants. The application of pesticides by unmanned aerial vehicles(UAV) can effectively avoid the harm caused by pesticides to human body, but the amount of pesticides is limited and it is difficult to locate the pesticides between flights. The unmanned navigation tractor with GNSS(global navigation satellite system) has realized the automatic navigation of planting and cotton harvesting in large area cotton field while could not work in cotton plant protection operation because the complex crop growth environment on site. Visual navigation vehicle can carry a large amount of pesticide, and its operation path is determined by the growth state of crops in the farmland avoiding crushing seedling. Therefore, it has great potential for the unmanned plant protection vehicle based on visual navigation in the field environment. Nowadays, sprayers mounted on tractors have being utilized in cotton protection in Xinjiang. The present studies for objects mainly focus on static images, and the dynamic detection of crop rows in video sequence is studied barely. Aiming at that, A plant protection unmanned vehicle was exploited, which can enhance and complement the intelligent agriculture. After the vehicle finish spraying in one cotton row, it will stop safely and accurately just at the edge of the proposed position. Subsequently, its 4 wheels will rotate 90° simultaneously, so as to ensure it can move in a vertical direction through the cotton rows; a camera on the opposite side can also be utilized to count the cotton rows and avoid repeated spraying. When the vehicle passes cotton rows preseted, its 4 wheels can simultaneously rotate 90°again along the same direction to prepare for the next spraying. Then a video-based dynamic count method for cotton rows is proposed to determine the interval distance of linear operation area in this paper. By tracking the centroids of cotton plant, the number of cotton rows could be counted in real time. Firstly, the color image from video became grayscale to emphasize information of cotton rows with prominent green component by calculation of 2 G-R-B. Then, a region of interest(ROI) was set not only to reduce the calculation amount, but also to avoid the lacking of seedling in the end of cotton rows. Secondly, the vertical cumulative histogram of gray in ROI was solved and the histogram vs ROI width curve was obtained. The wave crests of the curve determined by two conditions were found, in which the width and the sharpness should be satisfied with threshold. Then a floating window was established to positioning the cotton row. Besides that, the grayscale centroids of each floating window were calculated, which represent the cotton rows where each one was located. Thirdly, a target window with the size of 65×65 was established for each centroid. With the growth of cotton, the branches and leaves intertwined in which situation, the gap between the 2 cotton rows became smaller, and the cotton leaves of one row were very loose. In this case, one cotton row might correspond to more than one target window. To avoiding the influences of the growth, the overlap rate was calculated between each 2 adjacent target windows. And the 2 target windows whose overlap rate meeting the condition(large than 0.1) should be merged together. It had been done until no overlapped rate meeting the conditions. Thus, each cotton row had been identified. For tracking, starting from the second frame, the overlap rate between each target window and other target windows from previous frame was judged, if it met the condition, the two target windows in the two successive frames were connected. Then the cotton row could be tracked. The test proved that the processing time of detecting cotton row was approximately 150 ms per frame, which satisfied the requirement of practical application for the cotton protection in the field.
Pesticide spraying is one of the most important farm activities related to the protection of plants. The application of pesticides by unmanned aerial vehicles(UAV) can effectively avoid the harm caused by pesticides to human body, but the amount of pesticides is limited and it is difficult to locate the pesticides between flights. The unmanned navigation tractor with GNSS(global navigation satellite system) has realized the automatic navigation of planting and cotton harvesting in large area cotton field while could not work in cotton plant protection operation because the complex crop growth environment on site. Visual navigation vehicle can carry a large amount of pesticide, and its operation path is determined by the growth state of crops in the farmland avoiding crushing seedling. Therefore, it has great potential for the unmanned plant protection vehicle based on visual navigation in the field environment. Nowadays, sprayers mounted on tractors have being utilized in cotton protection in Xinjiang. The present studies for objects mainly focus on static images, and the dynamic detection of crop rows in video sequence is studied barely. Aiming at that, A plant protection unmanned vehicle was exploited, which can enhance and complement the intelligent agriculture. After the vehicle finish spraying in one cotton row, it will stop safely and accurately just at the edge of the proposed position. Subsequently, its 4 wheels will rotate 90° simultaneously, so as to ensure it can move in a vertical direction through the cotton rows; a camera on the opposite side can also be utilized to count the cotton rows and avoid repeated spraying. When the vehicle passes cotton rows preseted, its 4 wheels can simultaneously rotate 90°again along the same direction to prepare for the next spraying. Then a video-based dynamic count method for cotton rows is proposed to determine the interval distance of linear operation area in this paper. By tracking the centroids of cotton plant, the number of cotton rows could be counted in real time. Firstly, the color image from video became grayscale to emphasize information of cotton rows with prominent green component by calculation of 2 G-R-B. Then, a region of interest(ROI) was set not only to reduce the calculation amount, but also to avoid the lacking of seedling in the end of cotton rows. Secondly, the vertical cumulative histogram of gray in ROI was solved and the histogram vs ROI width curve was obtained. The wave crests of the curve determined by two conditions were found, in which the width and the sharpness should be satisfied with threshold. Then a floating window was established to positioning the cotton row. Besides that, the grayscale centroids of each floating window were calculated, which represent the cotton rows where each one was located. Thirdly, a target window with the size of 65×65 was established for each centroid. With the growth of cotton, the branches and leaves intertwined in which situation, the gap between the 2 cotton rows became smaller, and the cotton leaves of one row were very loose. In this case, one cotton row might correspond to more than one target window. To avoiding the influences of the growth, the overlap rate was calculated between each 2 adjacent target windows. And the 2 target windows whose overlap rate meeting the condition(large than 0.1) should be merged together. It had been done until no overlapped rate meeting the conditions. Thus, each cotton row had been identified. For tracking, starting from the second frame, the overlap rate between each target window and other target windows from previous frame was judged, if it met the condition, the two target windows in the two successive frames were connected. Then the cotton row could be tracked. The test proved that the processing time of detecting cotton row was approximately 150 ms per frame, which satisfied the requirement of practical application for the cotton protection in the field.
引文
[1]姬长英,周俊.农业机械导航技术发展分析[J].农业机械学报,2014,45(9):44-54.Ji Changying,Zhou Jun.Current situation of navigation technologies for agricultural machinery[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(9):44-54.(in Chinese with English abstract)
[2]王涛,郝磊,臧秀法.我国植保机械技术发展探讨[J].农业科技与装备,2014(12):51-52.Wang Tao,Hao Lei,Zang Xiufa.Discussion on plant protection machinery technology development in China[J].Agricultural Science&Technology and Equipment,2014(12):51-52.(in Chinese with English abstract)
[3]刘刚,张晓辉,范国强,等.棉花施药机械的应用现状及发展趋势[J].农机化研究,2014,36(4):225-228.Liu Gang,Zhang Xiaohui,Fan Guoqiang,et al.Application status and development trend of cotton spraying machine[J].Journal of Agricultural Mechanization Research,2014,36(4):225-228.(in Chinese with English abstract)
[4]胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J].农业工程学报,2015,31(10):1-10.Hu Jingtao,Gao Lei,Bai Xiaoping,et al.Review of research on automatic guidance of agricultural vehicles[J].Transactions of the Chinese Society of Agricultural,2015,31(10):1-10.(in Chinese with English abstract)
[5]陈盛德,兰玉彬,李继宇,等.植保无人机航空喷施作业有效喷幅的评定与试验[J].农业工程学报,2017,33(7):82-90.Chen Shengde,Lan Yubin,Li Jiyu,et al.Evaluation and test of effective spraying width of aerial spraying on plant protection UAV[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(7):82-90.(in Chinese with English abstract)
[6]张宋超,薛新宇,秦维彩,等.N-3型农用无人直升机航空施药飘移模拟与试验[J].农业工程学报,2015,31(3):87-93.Zhang Songchao,Xue Xinyu,Qin Weicai,et al.Simulation and experimental verification of aerial spraying drift on N-3unmanned spraying helicopter[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(3):87-93.(in Chinese with English abstract)
[7]Sun H,Slaughter D C,Ruiz M P,et al.RTK GPS mapping of transplanted row crops[J].Computers and Electronics in Agriculture,2010,71(1):32-37.
[8]方震.GPS棉花铺膜播种机演示成功棉花铺膜播种机演成功[J].农业机械,2013(13):28.
[9]李丹阳,李彬,李江全.基于北斗导航、百度地图的采棉机监控系统设计[J].江苏农业科学,2015,43(9):455-457.
[10]胡炼,罗锡文,曾山,等.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[J].农业工程学报,2013,29(10):12-18.Hu Lian,Luo Xiwen,Zeng Shan,et al.Plant recognition and localization for intra-row mechanical weeding device base on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(10):12-18.(in Chinese with English abstract)
[11]孟庆宽,张漫,杨耿煌,等.自然光照下基于粒子群算法的农业机械导航路径识别[J].农业机械学报,2016,47(6):11-20.Meng Qingkuan,Zhang Man,Yang Genghuang,et al.Guidance line recognition of agricultural machinery based on particle swarm optimization under natural illumination[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(6):11-20.(in Chinese with English abstract)
[12]丁幼春,廖庆喜,黄海东,等.联合收获机大曲率路径视觉导航方法[J].农业机械学报,2011,42(S1):122-127.Ding Youchun,Liao Qingxi,Huang Haidong,et al.Large curvature path detection for combine harvester based on vision navigation[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(Supp.1):122-127.(in Chinese with English abstract)
[13]魏爽,李世超,张漫,等.基于GNSS的农机自动导航路径搜索及转向控制[J].农业工程学报,2017,33(增刊1):70-77.Wei Shuang,Li Shichao,Zhang Man,et al.Automatic navigation path search and turning control of agricultural machinery based on GNSS[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(Supp.1):70-77.(in Chinese with English abstract)
[14]孟庆宽,何洁,仇瑞承,等.基于机器视觉的自然环境下作物行识别与导航线提取[J].光学学报,2014,34(7):180-186.Meng Qingkuan,He Jie,Qiu Ruicheng,et al.Crop recognition and navigation line detection in natural environment based on machine vision[J].Acta Optica Sinica,2014,34(7):180-186.(in Chinese with English abstract)
[15]Zhang Q,Qiu H C.A dynamic path search algorithm for tractor automatic navigation[J].Transactions of the ASAE,2004,47(2):639-646.
[16]赵颖,陈兵旗,王书茂,等.基于机器视觉的耕作机器人行走目标直线检测[J].农业机械学报,2006,37(4):83-86.Zhao Ying,Chen Bingqi,Wang Shumao,et al.Fast detection of furrows based on machine vision on autonomous mobile robot[J].Transactions of the Chinese Society for Agricultural Machinery,2006,37(4):83-86.(in Chinese with English abstract)
[17]江锽,肖爱平.喷药机器人在温室中道路识别及边界提取的研究[J].林业机械与木工设备,2014,42(10):18-21.Jiang Huang,Xiao Aiping.Study on spraying robot’s road recognition and boundary extraction in greenhouses[J].Forestry Machinery&Woodworking Equipment,2014,42(10):18-21.(in Chinese with English abstract)
[18]宁松瑞,左强,石建初,等.新疆典型膜下滴灌棉花种植模式的用水效率与效益[J].农业工程学报,2013,29(22):90-99.Ning Songrui,Zuo Qiang,Shi Jianchu,et al.Water use efficiency and benefit for typical planting modes of drip-irrigated cotton under film in Xinjiang[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(22):90-99.(in Chinese with English abstract)
[19]陈晨,薛新宇,顾伟,等.喷雾机喷杆结构形状及截面尺寸优化与试验[J].农业工程学报,2015,31(9):50-56.Chen Chen,Xue Xinyu,Gu Wei,et al.Experiment and structure shape and section size optimization of spray boom[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(9):50-56.(in Chinese with English abstract)
[20]苏伟,蒋坤萍,闫安,等.基于无人机遥感影像的育种玉米垄数统计监测[J].农业工程学报,2018,34(10):92-98.Su Wei,Jiang Kunping,Yan An,et al.Monitoring of planted lines for breeding corn using UAV remote sensing image[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2018,34(10):92-98.(in Chinese with English abstract)
[21]Wang Q,Zhang Q,Rovira-Más,et al.Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields[J].Biosystems Engineering,2011,109(4):258-265.
[22]吕丽平,张西芝,张玉宏.基于中心线引导的主动视觉导航方法研究[J].电子测量与仪器学报,2018,32(3):18-25.LüLiping,Zhang Xizhi,Zhang Yuhong.Research of active vision navigation based on centerline guidance[J].Journal of Electronic Measurement and Instrumentation,2018,32(3):18-25.(in Chinese with English abstract)
[23]李林,魏新华,朱文静,等.宽幅施药机械机器视觉辅助导航系统研究[J].农业机械学报,2015,46(9):28-33.Li Lin,Wei Xinhua,Zhu Wenjing,et al.Research on auxiliary navigation system for wide spraying mechanism based on machine vision[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(9):28-33.(in Chinese with English abstract)
[24]闫辉,许廷发,吴青青,等.多特征融合匹配的多目标跟踪[J].中国光学,2013,6(2):163-170.Yan Hui,Xu Tingfa,Wu Qingqing,et al.Multi-object tracking based on multi-feature joint matching[J].Chinese Optics,2013,6(2):163-170.(in Chinese with English abstract)
[25]白如月,汪小旵,鲁伟,等.施药机器人对行施药系统的设计与试验[J].华南农业大学学报,2018,39(5):101-109.Bai Ruyue,Wang Xiaochan,Lu Wei,et al.Design and experiment of row-following pesticide spraying system by robot[J].Journal of South China Agricultural University,2018,39(5):101-109.(in Chinese with English abstract)
[26]孙巧.基于加权重叠率的单目标视觉跟踪评价指标[J].电子学报,2017,45(3):753-761.
[27]吴刚,谭彧,郑永军,等.基于改进Hough变换的收获机器人行走目标直线检测[J].农业机械学报,2010,41(2):176-179.Wu Gang,Tan Yu,Zheng Yongjun,et al.Walking goal line detection based on improved Hough transform on harvesting robot[J].Transactions of the Chinese Society for Agricultural Machinery,2010,41(2):176-179.(in Chinese with English abstract)
[28]彭顺正,坎杂,李景彬.矮化密植枣园收获作业视觉导航路径提取[J].农业工程学报,2017,33(9):45-52.Peng Shunzheng,Kan Za,Li Jingbin.Extraction of visual navigation directrix for harvesting operation in short-stalked and close-planting jujube orchard[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(9):45-52.(in Chinese with English abstract)
[29]刘士建,吴滢跃.具有记忆跟踪功能的质心跟踪算法[J].红外技术,2012,34(11):636-639.Liu Shijian,Wu Yingyue.Centroid tracking algorithm with memory tracking feature[J].Infrared Technology,2012,34(11):636-639.(in Chinese with English abstract)
[30]梁习卉子,陈兵旗,姜秋慧,等.基于图像处理的玉米收割机导航路线检测方法[J].农业工程学报,2016,32(22):43-49.Liang Xihuizi,Chen Bingqi,Jiang Qiuhui,et al.Detection method of navigation route of corn harvester based on image processing[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2016,32(22):43-49.(in Chinese with English abstract)
[31]路红,李宏胜,费树岷,等.融合块显著质心描述和多级关联的多目标跟踪[J].系统工程与电子技术,2015,37(9):2182-2190.Lu Hong,Li Hongsheng,Fei Shumin,et al.Block-level saliency centroid representation and multi-level association based multi-target tracking[J].Systems Engineering and Electronics,2015,37(9):2182-2190.(in Chinese with English abstract)
[32]张勤,陈少杰,李彬.基于SUSAN角点的秧苗列中心线提取方法[J].农业工程学报,2015,31(20):165-171.Zhang Qin,Chen Shaojie,Li Bin.Extraction method for centerlines of rice seedlings based on SUSAN corner[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(20):165-171.(in Chinese with English abstract)
[33]Ji Ronghua,Qi Lijun.Crop-row detection algorithm based on random Hough transformation[J].Mathematical and Computer Modelling,2011,54(3):1016-1020.
[34]Jiang Guoquan,Wang Zhiheng,Liu Hongmin.Automatic detection of crop rows based on multi-ROIs[J].Expert Systems with Applications,2015,42(5):2429-2441.
[2]王涛,郝磊,臧秀法.我国植保机械技术发展探讨[J].农业科技与装备,2014(12):51-52.Wang Tao,Hao Lei,Zang Xiufa.Discussion on plant protection machinery technology development in China[J].Agricultural Science&Technology and Equipment,2014(12):51-52.(in Chinese with English abstract)
[3]刘刚,张晓辉,范国强,等.棉花施药机械的应用现状及发展趋势[J].农机化研究,2014,36(4):225-228.Liu Gang,Zhang Xiaohui,Fan Guoqiang,et al.Application status and development trend of cotton spraying machine[J].Journal of Agricultural Mechanization Research,2014,36(4):225-228.(in Chinese with English abstract)
[4]胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J].农业工程学报,2015,31(10):1-10.Hu Jingtao,Gao Lei,Bai Xiaoping,et al.Review of research on automatic guidance of agricultural vehicles[J].Transactions of the Chinese Society of Agricultural,2015,31(10):1-10.(in Chinese with English abstract)
[5]陈盛德,兰玉彬,李继宇,等.植保无人机航空喷施作业有效喷幅的评定与试验[J].农业工程学报,2017,33(7):82-90.Chen Shengde,Lan Yubin,Li Jiyu,et al.Evaluation and test of effective spraying width of aerial spraying on plant protection UAV[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(7):82-90.(in Chinese with English abstract)
[6]张宋超,薛新宇,秦维彩,等.N-3型农用无人直升机航空施药飘移模拟与试验[J].农业工程学报,2015,31(3):87-93.Zhang Songchao,Xue Xinyu,Qin Weicai,et al.Simulation and experimental verification of aerial spraying drift on N-3unmanned spraying helicopter[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(3):87-93.(in Chinese with English abstract)
[7]Sun H,Slaughter D C,Ruiz M P,et al.RTK GPS mapping of transplanted row crops[J].Computers and Electronics in Agriculture,2010,71(1):32-37.
[8]方震.GPS棉花铺膜播种机演示成功棉花铺膜播种机演成功[J].农业机械,2013(13):28.
[9]李丹阳,李彬,李江全.基于北斗导航、百度地图的采棉机监控系统设计[J].江苏农业科学,2015,43(9):455-457.
[10]胡炼,罗锡文,曾山,等.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[J].农业工程学报,2013,29(10):12-18.Hu Lian,Luo Xiwen,Zeng Shan,et al.Plant recognition and localization for intra-row mechanical weeding device base on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(10):12-18.(in Chinese with English abstract)
[11]孟庆宽,张漫,杨耿煌,等.自然光照下基于粒子群算法的农业机械导航路径识别[J].农业机械学报,2016,47(6):11-20.Meng Qingkuan,Zhang Man,Yang Genghuang,et al.Guidance line recognition of agricultural machinery based on particle swarm optimization under natural illumination[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(6):11-20.(in Chinese with English abstract)
[12]丁幼春,廖庆喜,黄海东,等.联合收获机大曲率路径视觉导航方法[J].农业机械学报,2011,42(S1):122-127.Ding Youchun,Liao Qingxi,Huang Haidong,et al.Large curvature path detection for combine harvester based on vision navigation[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(Supp.1):122-127.(in Chinese with English abstract)
[13]魏爽,李世超,张漫,等.基于GNSS的农机自动导航路径搜索及转向控制[J].农业工程学报,2017,33(增刊1):70-77.Wei Shuang,Li Shichao,Zhang Man,et al.Automatic navigation path search and turning control of agricultural machinery based on GNSS[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(Supp.1):70-77.(in Chinese with English abstract)
[14]孟庆宽,何洁,仇瑞承,等.基于机器视觉的自然环境下作物行识别与导航线提取[J].光学学报,2014,34(7):180-186.Meng Qingkuan,He Jie,Qiu Ruicheng,et al.Crop recognition and navigation line detection in natural environment based on machine vision[J].Acta Optica Sinica,2014,34(7):180-186.(in Chinese with English abstract)
[15]Zhang Q,Qiu H C.A dynamic path search algorithm for tractor automatic navigation[J].Transactions of the ASAE,2004,47(2):639-646.
[16]赵颖,陈兵旗,王书茂,等.基于机器视觉的耕作机器人行走目标直线检测[J].农业机械学报,2006,37(4):83-86.Zhao Ying,Chen Bingqi,Wang Shumao,et al.Fast detection of furrows based on machine vision on autonomous mobile robot[J].Transactions of the Chinese Society for Agricultural Machinery,2006,37(4):83-86.(in Chinese with English abstract)
[17]江锽,肖爱平.喷药机器人在温室中道路识别及边界提取的研究[J].林业机械与木工设备,2014,42(10):18-21.Jiang Huang,Xiao Aiping.Study on spraying robot’s road recognition and boundary extraction in greenhouses[J].Forestry Machinery&Woodworking Equipment,2014,42(10):18-21.(in Chinese with English abstract)
[18]宁松瑞,左强,石建初,等.新疆典型膜下滴灌棉花种植模式的用水效率与效益[J].农业工程学报,2013,29(22):90-99.Ning Songrui,Zuo Qiang,Shi Jianchu,et al.Water use efficiency and benefit for typical planting modes of drip-irrigated cotton under film in Xinjiang[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2013,29(22):90-99.(in Chinese with English abstract)
[19]陈晨,薛新宇,顾伟,等.喷雾机喷杆结构形状及截面尺寸优化与试验[J].农业工程学报,2015,31(9):50-56.Chen Chen,Xue Xinyu,Gu Wei,et al.Experiment and structure shape and section size optimization of spray boom[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(9):50-56.(in Chinese with English abstract)
[20]苏伟,蒋坤萍,闫安,等.基于无人机遥感影像的育种玉米垄数统计监测[J].农业工程学报,2018,34(10):92-98.Su Wei,Jiang Kunping,Yan An,et al.Monitoring of planted lines for breeding corn using UAV remote sensing image[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2018,34(10):92-98.(in Chinese with English abstract)
[21]Wang Q,Zhang Q,Rovira-Más,et al.Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields[J].Biosystems Engineering,2011,109(4):258-265.
[22]吕丽平,张西芝,张玉宏.基于中心线引导的主动视觉导航方法研究[J].电子测量与仪器学报,2018,32(3):18-25.LüLiping,Zhang Xizhi,Zhang Yuhong.Research of active vision navigation based on centerline guidance[J].Journal of Electronic Measurement and Instrumentation,2018,32(3):18-25.(in Chinese with English abstract)
[23]李林,魏新华,朱文静,等.宽幅施药机械机器视觉辅助导航系统研究[J].农业机械学报,2015,46(9):28-33.Li Lin,Wei Xinhua,Zhu Wenjing,et al.Research on auxiliary navigation system for wide spraying mechanism based on machine vision[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(9):28-33.(in Chinese with English abstract)
[24]闫辉,许廷发,吴青青,等.多特征融合匹配的多目标跟踪[J].中国光学,2013,6(2):163-170.Yan Hui,Xu Tingfa,Wu Qingqing,et al.Multi-object tracking based on multi-feature joint matching[J].Chinese Optics,2013,6(2):163-170.(in Chinese with English abstract)
[25]白如月,汪小旵,鲁伟,等.施药机器人对行施药系统的设计与试验[J].华南农业大学学报,2018,39(5):101-109.Bai Ruyue,Wang Xiaochan,Lu Wei,et al.Design and experiment of row-following pesticide spraying system by robot[J].Journal of South China Agricultural University,2018,39(5):101-109.(in Chinese with English abstract)
[26]孙巧.基于加权重叠率的单目标视觉跟踪评价指标[J].电子学报,2017,45(3):753-761.
[27]吴刚,谭彧,郑永军,等.基于改进Hough变换的收获机器人行走目标直线检测[J].农业机械学报,2010,41(2):176-179.Wu Gang,Tan Yu,Zheng Yongjun,et al.Walking goal line detection based on improved Hough transform on harvesting robot[J].Transactions of the Chinese Society for Agricultural Machinery,2010,41(2):176-179.(in Chinese with English abstract)
[28]彭顺正,坎杂,李景彬.矮化密植枣园收获作业视觉导航路径提取[J].农业工程学报,2017,33(9):45-52.Peng Shunzheng,Kan Za,Li Jingbin.Extraction of visual navigation directrix for harvesting operation in short-stalked and close-planting jujube orchard[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2017,33(9):45-52.(in Chinese with English abstract)
[29]刘士建,吴滢跃.具有记忆跟踪功能的质心跟踪算法[J].红外技术,2012,34(11):636-639.Liu Shijian,Wu Yingyue.Centroid tracking algorithm with memory tracking feature[J].Infrared Technology,2012,34(11):636-639.(in Chinese with English abstract)
[30]梁习卉子,陈兵旗,姜秋慧,等.基于图像处理的玉米收割机导航路线检测方法[J].农业工程学报,2016,32(22):43-49.Liang Xihuizi,Chen Bingqi,Jiang Qiuhui,et al.Detection method of navigation route of corn harvester based on image processing[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2016,32(22):43-49.(in Chinese with English abstract)
[31]路红,李宏胜,费树岷,等.融合块显著质心描述和多级关联的多目标跟踪[J].系统工程与电子技术,2015,37(9):2182-2190.Lu Hong,Li Hongsheng,Fei Shumin,et al.Block-level saliency centroid representation and multi-level association based multi-target tracking[J].Systems Engineering and Electronics,2015,37(9):2182-2190.(in Chinese with English abstract)
[32]张勤,陈少杰,李彬.基于SUSAN角点的秧苗列中心线提取方法[J].农业工程学报,2015,31(20):165-171.Zhang Qin,Chen Shaojie,Li Bin.Extraction method for centerlines of rice seedlings based on SUSAN corner[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(20):165-171.(in Chinese with English abstract)
[33]Ji Ronghua,Qi Lijun.Crop-row detection algorithm based on random Hough transformation[J].Mathematical and Computer Modelling,2011,54(3):1016-1020.
[34]Jiang Guoquan,Wang Zhiheng,Liu Hongmin.Automatic detection of crop rows based on multi-ROIs[J].Expert Systems with Applications,2015,42(5):2429-2441.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |