Early stage crop rows detection based on least square method

Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery

Volumn 41, Issue 7, 2010, Pages

  Si, Yongsheng ^a,b   Jiang, Guoquan ^c   Liu, Gang ^b   Gao, Rui ^b   Liu, Zhaoxiang ^b  

^a AGRICULTURAL UNIVERSITY OF HEBEI   (China)

^b CHINA AGRICULTURAL UNIVERSITY   (China)

^c HENAN POLYTECHNIC UNIVERSITY   (China)

Author keywords

Agricultural machinery; Image segmentation; Least square method; Line detection; Machine vision; Navigation

Indexed keywords

CENTER POINTS; CROP ROWS; CROP ROWS DETECTION; FEATURE POINT; LEAST SQUARE METHODS; LINE DETECTION; MACHINE VISION; REAL TIME PERFORMANCE; STAGE OF GROWTH; VEHICLE NAVIGATION; VERTICAL PROJECTION;

AGRICULTURAL MACHINERY; COMPUTER VISION; DIGITAL IMAGE STORAGE; IMAGE SEGMENTATION; LEAST SQUARES APPROXIMATIONS; NAVIGATION;

CROPS;

EID: 77955242854     PISSN: 10001298     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1000-1298.2010.07.034     Document Type: Article

References (13)

1. Zhao Bo, Wang Meng, Mao Enrong, et al. Recognition and classification for vision navigation application environment of agricultural vehicle[J]. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(7): 166-170. (in Chinese)
2. Hou Xuegui, Chen Yong, Guo Weibin. Machine vision-based navigation for a weeding robot[J]. Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(3): 106-108. (in Chinese)
3. Tijmen Bakkera, Hendrik Woutersa, Kees van Asselta, et al. A vision based row detection system for sugar beet[J]. Computers and Electronics in Agriculture, 2008, 60(1): 87-95.
4. Björn Astrand, Albert-Jan Baerveldt. A vision based row-following system for agricultural field machinery[J]. Mechatronics, 2005, 15(2): 251-269.
5. Rovira-Ma's F, Zhang Q, Reid J F, et al. Hough-transform-based vision algorithm for crop row detection of an automated agricultural vehicle[J]. Proceedings of the IMechE, Part D: Journal of Automobile Engineering, 2005, 219(8): 999-1010.
6. Zhao Ruijiao, Li Minzan, Zhang Man, et al. Rapid crop-row detection based on improved hough transformation[J]. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(7): 163-165, 221. (in Chinese)
7. Leemans V, Destain M F. Line cluster detection using a variant of the Hough transform for culture row localization[J]. Image and Vision Computing, 2006, 24(5): 541-550
8. Zhang Lei, Wang Shumao, Chen Bingqi, et al. Edge detection for wheat field based on machine vision[J]. Transactions of the Chinese Society for Agricultural Machinery, 2007, 38(2): 111-114. (in Chinese)
9. Søgaard H T, Olsen H J. Determination of crop rows by image analysis without segmentation[J]. Computers and Electronics in Agriculture, 2003, 38(2): 141-158.
10. Yuan Zuoyun, Mao Zhihuai, Wei Qing. Orientation technique of crop rows based on computer vision[J]. Journal of China Agricultural University, 2005, 10(3): 69-72. (in Chinese)
11. Zhang Zhibin, Luo Xiwen, Li Qing, et al. New algorithm for machine vision navigation of farm machine based on well-ordered set and crop row structure[J]. Transactions of the CSAE, 2007, 23(7): 122-126. (in Chinese)
12. Rao Honghui, Ji Changying. Research on precision band spraying system based on machine vision[J]. Acta Agriculture Jiangxi, 2007, 19(2): 63-65. (in Chinese)
13. Lei Xu, Erkki Oja, Pekka Kultanen. A new curve detection method: randomized Hough transform (RHT)[J]. Pattern Recognition Letters, 1990, 11(5): 331-338.