Crop rows detection based on parallel characteristic of crop rows using visual navigation

被引:0
作者
Chen, Jiao [1 ]
Jiang, Guoquan [2 ]
Du, Shangfeng [1 ]
Ke, Xing [1 ]
机构
[1] College of Information and Electrical Engineering, China Agricultural University
[2] School of Computer Science and Technology, Henan Polytechnic University
来源
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2009年 / 25卷 / 12期
关键词
Camera calibration; Crop rows detection; Hough Transform; Image processing; Machine vision; Navigation; Robots;
D O I
10.3969/j.issn.1002-6819.2009.12.019
中图分类号
学科分类号
摘要
To detect and localize the crop rows quickly and effectively for navigation of agricultural machines, a new algorithm for crop rows detection is proposed in this paper. A navigation software was developed in VC++ 6.0. Crop rows were separated from soil background by image pre-processing, and the localization points were got by vertical projection. The world coordinates of each localization point were computed according to the principle of perspective transformation and the camera calibration results. With the parallel characteristic of crop rows, an improved algorithm based on Hough Transform was employed for the detection and localization of crop rows. The experiment with images of crop rows and the simulation experiment in laboratory showed that the new algorithm took 219.4 ms to process a 320×240 pixels color image, and the average errors of navigation distance and navigation angle were 2.33 mm and 0.3°. The experimental results confirmed that the algorithm was accurate, effective and fast enough to detect and localize crop rows for real-time navigation.
引用
收藏
页码:107 / 113
页数:6
相关论文
共 15 条
  • [1] Zhang Z., Luo X., Li Q., Et al., New algorithm for machine vision navigation oI farm machine based on well-ordered set and crop row structure, Transactions of the CSAE, 23, 7, pp. 122-126, (2007)
  • [2] Tillett N.D., Hague T., Marchant J.A., A Robotic system for Plant-Scale Husbandry, J Agric Eng Res, 69, 2, pp. 169-178, (1998)
  • [3] Zhang Z., Luo X., Zhou X., Et al., Crop rows detection based on Hough transform and fisher discriminant criterion function, Journal of Image and Graghics, 12, 12, pp. 2164-2168, (2007)
  • [4] Pla F., Sanchiz J.M., Marchant J.A., Et al., Building perspective models to guide a row crop navigation vehicle, Image and Vision Computing, 15, 6, pp. 465-470, (1997)
  • [5] Leemans V., Destain M.F., Line cluster detection using a vartiant of the Hough transform for culture row localisation, Image and Vision Computing, 24, 5, pp. 541-550, (2006)
  • [6] Geech, Bossu J., Jones G., Et al., Crop/weed discrimination in perspective agronomic image, Computers and Electronics in Agriculture, 58, 1, pp. 1-92, (2007)
  • [7] Xu L., Oja E., Randomized Hough transform(RHT): basic mechanisms, algorithms,and computational complexities, CVGIP-Image Understanding, 57, 2, pp. 131-154, (1993)
  • [8] Woebbecke D.M., Meyer G.E., Von Bargen, Et al., Color indices for weed identification under various soil, residue, and lighting conditions, Transactions of the ASAE, 38, 1, pp. 259-269, (1995)
  • [9] Zhang W., Du S., Machine vision recognizing position baseline in cropland, Journal of China Agricultural University, 11, 4, pp. 75-77, (2006)
  • [10] Yuan Z., Mao Z., Wei Q., Orientation technique of crop rows based on computer vision, Journal of China Agricultural University, 10, 3, pp. 69-72, (2005)