基于无人机的田间地膜识别算法研究
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摘要
为了满足基于机器视觉的田间地膜智能识别要求,对垂直拍摄的6叶期单垄单行烟田图像进行研究,分析图像中地膜、烟苗和土壤的RGB和HSV分量的直方图,发现B分量和V分量采用阈值分割法能分割出地膜。对地膜图像进行手动阈值分割、迭代阈值分割、大律法分割和基于遗传算法的最大熵值法等分割算法比较,发现迭代阈值分割算法目标识别率最高,为71%,且处理过程用时较短。通过对无人机不同飞行高度下地膜识别情况分析,发现50 m飞行高度下的地膜识别率最高,为80.06%,地膜识别面积为246.83 m~2,地膜覆盖率为30.12%。该研究为残膜的智能识别提供方法和参考。
In order to meet the requirements of intelligent recognition of field mulch film based on machine vision, the images were taken vertically by unmanned aerial vehicle(UAV) to the tobacco seedlings with mulch film in the field. The component color information histograms based on RGB and HSV color model of mulch film, tobacco seedlings and soil were analyzed. The color information of B component and V component was able to identify mulch film from background with the threshold segmentation method. The manual threshold segmentation, iterative threshold segmentation, large-law segmentation and maximum entropy method based on genetic algorithm were compared. Results showed that the iterative threshold segmentation algorithm had the highest target recognition rate of 71%, and the processing time was the shortest. The mulch film recognition rates under different flight heights was analyzed and figured out. It was found that the film recognition rate at 50 m flight height was the highest as 80.06%, the film recognition area was 246.83 m~2, and the film coverage rate was 30.12%. This research provided a method and reference for intelligent identification of mulch film and residual membrane with crop based on UAV.
In order to meet the requirements of intelligent recognition of field mulch film based on machine vision, the images were taken vertically by unmanned aerial vehicle(UAV) to the tobacco seedlings with mulch film in the field. The component color information histograms based on RGB and HSV color model of mulch film, tobacco seedlings and soil were analyzed. The color information of B component and V component was able to identify mulch film from background with the threshold segmentation method. The manual threshold segmentation, iterative threshold segmentation, large-law segmentation and maximum entropy method based on genetic algorithm were compared. Results showed that the iterative threshold segmentation algorithm had the highest target recognition rate of 71%, and the processing time was the shortest. The mulch film recognition rates under different flight heights was analyzed and figured out. It was found that the film recognition rate at 50 m flight height was the highest as 80.06%, the film recognition area was 246.83 m~2, and the film coverage rate was 30.12%. This research provided a method and reference for intelligent identification of mulch film and residual membrane with crop based on UAV.
引文
[1] 王浦舟,吴雪梅,张富贵,等.梳齿式自动仿形残膜捡拾机的设计及性能试验[J].中国烟草学报,2017,23(3):56-62.WANG P Z,WU X M,ZHANG F G,et al.Design and performance test of comb-type automatic profiling residual film collecting machine[J].Acta Tabacaria Sinica,2017,23(3):56-62.(in Chinese with English abstract)
[2] 李明洋,马少辉.我国残膜回收机研究现状及建议[J].农机化研究,2014,36(6):242-245,252.LI M Y,MA S H.Present situation of research on plastic film residue collector in China and some suggestions[J].Journal of Agricultural Mechanization Research,2014,36 (6):242-245,252.(in Chinese with English abstract)
[3] 张会敏,谢泽奇,张善文,等.基于WT-Otsu算法的植物病害叶片图像分割方法[J].江苏农业科学,2017,45(18):194-196.ZHANG H M,XIE Z Q,ZHANG S W,et al.Image segmentation method for plant disease leaves based on WT-Otsu algorithm[J].Jiangsu Agricultural Sciences,2017,45 (18):194-196.(in Chinese with English abstract)
[4] 路阳,衣淑娟,张勇,等.基于PCA和Whitening算法的水稻病害图像预处理研究[J].黑龙江八一农垦大学学报,2017,29(2):97-101.LU Y,YI S J,ZHANG Y,et al.Research of rice disease image preprocessing based on PCA and whitening algorithm[J].Journal of Heilongjiang Bayi Agricultural University,2017,29 (2):97-101.(in Chinese with English abstract)
[5] 张航.基于高光谱成像技术的皮棉中地膜识别方法研究[D].北京:中国农业大学,2016.ZHANG H.Identification of plastic films in ginned cotton based on hyperspectral imaging technique [D].Beijing:China Agricultural University,2016.(in Chinese with English abstract)
[6] 哈斯图亚.基于多源数据的地膜覆盖农田遥感识别研究[D].北京:中国农业科学院,2017.HASITUYA.Mapping plastic-mulched farmland with multi-source remote sensing data [D].Beijing:Chinese Academy of Agricultural Sciences,2017.(in Chinese with English abstract)
[7] 裘友荣.相对熵在图像去噪中的应用[J].遥感信息,2018,33(3):124-129.QIU Y R.Image denoising based on symmetric Kullback-Leibler divergence[J].Remote Sensing Information,2018,33 (3):124-129.(in Chinese with English abstract)
[8] 张真真,王建林.结合第二代Bandelet变换分块的字典学习图像去噪算法[J].计算机科学,2018,45(7):264-270.ZHANG Z Z,WANG J L.Dictionary learning image denoising algorithm combining second generation Bandelet transform block[J].Computer Science,2018,45(7):264-270.(in Chinese with English abstract)
[9] 谭小刚,张洪伟.基于小尺度分形维数的裂缝图像分割方法[J].公路交通科技,2018,35(5):34-39.TAN X G,ZHANG H W.A crack image segmentation method based on small scale fractal dimension[J].Journal of Highway and Transportation Research and Development,2018,35 (5):34-39.(in Chinese with English abstract)
[10] 李俊峰.基于RGB色彩空间自然场景统计的无参考图像质量评价[J].自动化学报,2015,41(9):1601-1615.LI J F.No-reference image quality assessment based on natural scene statistics in RGB color space[J].Acta Automatica Sinica,2015,41 (9):1601-1615.(in Chinese with English abstract)
[11] 陈祖刚,巴图娜存,徐芝英,等.基于数码相机的草地植被盖度测量方法对比研究[J].草业学报,2014,23(6):20-27.CHEN Z G,BATU N C,XU Z Y,et al.Measuring grassland vegetation cover using digital camera images[J].Acta Prataculturae Sinica,2014,23 (6):20-27.(in Chinese with English abstract)
[12] 张永玲,姜梦洲,俞佩仕,等.基于多特征融合和稀疏表示的农业害虫图像识别方法[J].中国农业科学,2018,51(11):2084-2093.ZHANG Y L,JIANG M Z,YU P S,et al.Agricultural pest identification based on multi-feature fusion and sparse representation[J].Scientia Agricultura Sinica,2018,51 (11):2084-2093.(in Chinese with English abstract)
[13] 彭志勇,常发亮,刘洪彬,等.基于HSV模型和特征点匹配的行人重识别算法[J].光电子·激光,2015,26(8):1575-1582.PENG Z Y,CHANG F L,LIU H B,et al.Person re-identification algorithm based on HSV model and keypoints matching[J].Journal of Optoelectronics·Laser,2015,26 (8):1575-1582.(in Chinese with English abstract)
[14] 李长春,都伟冰,马潇潇,等.改进马尔可夫模型的SAR图像分割[J].遥感信息,2017,32(6):85-89.LI C C,DU W B,MA X X,et al.SAR image segmentation based on improved MRF model[J].Remote Sensing Information,2017,32 (6):85-89.(in Chinese with English abstract)
[15] 徐正光,鲍东来,张利欣.基于递归的二值图像连通域像素标记算法[J].计算机工程,2006,32(24):186-188,225.XU Z G,BAO D L,ZHANG L X.Pixel labeled algorithm based on recursive method of connecting area in binary images[J].Computer Engineering,2006,32(24):186-188,225.(in Chinese with English abstract)
[16] 甘玲,林小晶.基于连通域提取的车牌字符分割算法[J].计算机仿真,2011,28(4):336-339.GAN L,LIN X J.License plate character segmentation based on connected component extraction[J].Computer Simulation,2011,28 (4):336-339.(in Chinese with English abstract)
[2] 李明洋,马少辉.我国残膜回收机研究现状及建议[J].农机化研究,2014,36(6):242-245,252.LI M Y,MA S H.Present situation of research on plastic film residue collector in China and some suggestions[J].Journal of Agricultural Mechanization Research,2014,36 (6):242-245,252.(in Chinese with English abstract)
[3] 张会敏,谢泽奇,张善文,等.基于WT-Otsu算法的植物病害叶片图像分割方法[J].江苏农业科学,2017,45(18):194-196.ZHANG H M,XIE Z Q,ZHANG S W,et al.Image segmentation method for plant disease leaves based on WT-Otsu algorithm[J].Jiangsu Agricultural Sciences,2017,45 (18):194-196.(in Chinese with English abstract)
[4] 路阳,衣淑娟,张勇,等.基于PCA和Whitening算法的水稻病害图像预处理研究[J].黑龙江八一农垦大学学报,2017,29(2):97-101.LU Y,YI S J,ZHANG Y,et al.Research of rice disease image preprocessing based on PCA and whitening algorithm[J].Journal of Heilongjiang Bayi Agricultural University,2017,29 (2):97-101.(in Chinese with English abstract)
[5] 张航.基于高光谱成像技术的皮棉中地膜识别方法研究[D].北京:中国农业大学,2016.ZHANG H.Identification of plastic films in ginned cotton based on hyperspectral imaging technique [D].Beijing:China Agricultural University,2016.(in Chinese with English abstract)
[6] 哈斯图亚.基于多源数据的地膜覆盖农田遥感识别研究[D].北京:中国农业科学院,2017.HASITUYA.Mapping plastic-mulched farmland with multi-source remote sensing data [D].Beijing:Chinese Academy of Agricultural Sciences,2017.(in Chinese with English abstract)
[7] 裘友荣.相对熵在图像去噪中的应用[J].遥感信息,2018,33(3):124-129.QIU Y R.Image denoising based on symmetric Kullback-Leibler divergence[J].Remote Sensing Information,2018,33 (3):124-129.(in Chinese with English abstract)
[8] 张真真,王建林.结合第二代Bandelet变换分块的字典学习图像去噪算法[J].计算机科学,2018,45(7):264-270.ZHANG Z Z,WANG J L.Dictionary learning image denoising algorithm combining second generation Bandelet transform block[J].Computer Science,2018,45(7):264-270.(in Chinese with English abstract)
[9] 谭小刚,张洪伟.基于小尺度分形维数的裂缝图像分割方法[J].公路交通科技,2018,35(5):34-39.TAN X G,ZHANG H W.A crack image segmentation method based on small scale fractal dimension[J].Journal of Highway and Transportation Research and Development,2018,35 (5):34-39.(in Chinese with English abstract)
[10] 李俊峰.基于RGB色彩空间自然场景统计的无参考图像质量评价[J].自动化学报,2015,41(9):1601-1615.LI J F.No-reference image quality assessment based on natural scene statistics in RGB color space[J].Acta Automatica Sinica,2015,41 (9):1601-1615.(in Chinese with English abstract)
[11] 陈祖刚,巴图娜存,徐芝英,等.基于数码相机的草地植被盖度测量方法对比研究[J].草业学报,2014,23(6):20-27.CHEN Z G,BATU N C,XU Z Y,et al.Measuring grassland vegetation cover using digital camera images[J].Acta Prataculturae Sinica,2014,23 (6):20-27.(in Chinese with English abstract)
[12] 张永玲,姜梦洲,俞佩仕,等.基于多特征融合和稀疏表示的农业害虫图像识别方法[J].中国农业科学,2018,51(11):2084-2093.ZHANG Y L,JIANG M Z,YU P S,et al.Agricultural pest identification based on multi-feature fusion and sparse representation[J].Scientia Agricultura Sinica,2018,51 (11):2084-2093.(in Chinese with English abstract)
[13] 彭志勇,常发亮,刘洪彬,等.基于HSV模型和特征点匹配的行人重识别算法[J].光电子·激光,2015,26(8):1575-1582.PENG Z Y,CHANG F L,LIU H B,et al.Person re-identification algorithm based on HSV model and keypoints matching[J].Journal of Optoelectronics·Laser,2015,26 (8):1575-1582.(in Chinese with English abstract)
[14] 李长春,都伟冰,马潇潇,等.改进马尔可夫模型的SAR图像分割[J].遥感信息,2017,32(6):85-89.LI C C,DU W B,MA X X,et al.SAR image segmentation based on improved MRF model[J].Remote Sensing Information,2017,32 (6):85-89.(in Chinese with English abstract)
[15] 徐正光,鲍东来,张利欣.基于递归的二值图像连通域像素标记算法[J].计算机工程,2006,32(24):186-188,225.XU Z G,BAO D L,ZHANG L X.Pixel labeled algorithm based on recursive method of connecting area in binary images[J].Computer Engineering,2006,32(24):186-188,225.(in Chinese with English abstract)
[16] 甘玲,林小晶.基于连通域提取的车牌字符分割算法[J].计算机仿真,2011,28(4):336-339.GAN L,LIN X J.License plate character segmentation based on connected component extraction[J].Computer Simulation,2011,28 (4):336-339.(in Chinese with English abstract)