Weed detection using image processing under different illumination for site-specific areas spraying

Computers and Electronics in Agriculture

Volumn 122, Issue , 2016, Pages 103-111

  Tang, Jing Lei ^a   Chen, Xiao Qian ^a   Miao, Rong Hui ^a   Wang, Dong ^a  

^a NORTHWEST A F UNIVERSITY   (China)

Author keywords

Bayesian decision; Center line of crop rows; Color space; Different illumination; Fixed point spraying; Weed Infestation Rate

Indexed keywords

COLOR; CROPS; HERBICIDES; IMAGE PROCESSING; NORMAL DISTRIBUTION; PLANNING; SUSTAINABLE DEVELOPMENT;

BAYESIAN DECISION; COLOR SPACE; CROP ROWS; FIXED POINTS; WEED INFESTATION;

WEED CONTROL;

ACCURACY ASSESSMENT; ALGORITHM; BAYESIAN ANALYSIS; HERBICIDE; IMAGE PROCESSING; NUMERICAL MODEL; PESTICIDE APPLICATION; SUSTAINABLE DEVELOPMENT; WEED CONTROL;

EID: 84957093240     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2015.12.016     Document Type: Article

References (21)

1. Duan R.Q., Zhao W., Huang S.L., Chen J.Y. Fast line detection algorithm based on improved Hough transformation. Chin. J. Sci. Instrum. 2010, 31(12):2774-2779.
2. Gebhardt S., Khbauch W. A new algorithm for automatic rumex obtusifolius detection in digital images using colour and texture features and the influence of image resolution. Precision Agric. 2007, 8(1-2):1-13.
3. Ghazali K.H.B., Ma J., Xiao R., Lubis S.A. An innovative face detection based on YCGCR color space. Phys. Procedia 2012, 25.
4. He D.J., Geng N., Zhang Y.K. Digital Image Processing 2008, Xian University of Electronic Science and Technology Press.
5. Huang S.K., Qi L.J., Zhang J.H., Wang J. An identification algorithm of weeds among multi-row corn based on the mapping of the corn rows width. Chin. J. China Agric. Univ. 2013, 18(1):165-171.
6. Li Y. Svm-based weed identification using field imaging spectral data. Chin. J. Remote Sens. Inform. 2014, 29(1):40-50.
7. Lin W.M., Hu Y.T. Image segmentation method based on YUV color space for tomato harvesting robot. Chin. J. Trans. Chin. Soc. Agric. Mach. 2012, 43(12):176-180.
8. Liu Z.Z., Xu X.Y., Wu Q.F. A novel k-nearest neighbor algorithm based on i-divergence criterion. ICIC Express Lett. 2013, 4(2):343-348.
9. Manh A.-G., Rabatel G., Assemat L., Aldon M.-J. Weed leaf image segmentation by deformable templates. J. Agric. Eng. Res. 2001, 80(2):139-146.
10. Meng Q.K., He J., Chou R.C., Ma X.D., Si Y.S., Liu M.Z.G. Color image segmentation method based on RGB color space. Chin. J. Acta Opt. Sinica 2014, 34(7):180-186.
11. Pla F., Sanchiz J.M., Marchant J.A., Brivot R. Building perspective models to guide a row crop navigation vehicle. Image Vis. Comput. 1997, 15(6):465-473.
12. Tellaeche A., Xavier P., Burgos-Artizzu, Pajares G., Ribeiro A. A vision-based method for weeds identification through the bayesian decision theory. Pattern Recogn. 2008, 41(2):521-530.
13. Tellaeche A., Pajares G., Burgos-Artizzu X.P., Ribeiro A. A computer vision approach for weeds identification through support vector machines. Appl. Soft Comput. 2011, 11(1):908-915.
14. Wei S.H., Wan Z.X., Wang K.J., Qiang S. The application and prospects of weeds in computer science. Chin. J. Weed Sci. 2012.
15. Wu, L.L., 2010. Research on identification for in-field weed/corn seedlings by digital image processing. Ph.D. thesis, Huazhong Agricultural University.
16. Xu, Y., 2013. Research on weed detection method for corn seedling stage. Master's thesis, Agricultural University.
17. Yang H.Q., Li M.G. An evaluation model for the field weed control based on bp neural network. Chin. J. Shandong Univ. Technol. (Nat. Sci. Ed.) 2014, 28(2):70-74.
18. Yang J., Zhu L. Color image segmentation method based on RGB color space. Chin. J. Jisuanji Xian Dai Hua 2010, (8):147-150.
19. Yuan Z.Y., Mao Z.H., Wei Q. Orientation technique of crop rows based on computer vision. Chin. J. China Agric. Univ. 2005, 10(3):69-72.
20. Zhang K., Wang X.Y., Wang Z.Q. Harmful of field weeds and control technology. Chin. J. Modern Agric. 2011, 31(1):12-13.
21. Zhao C.J., Xue X.Z., Wang X., Chen L.P., Pan Y.C., Meng Z.J. Advance and prospects of precision agriculture technology system. Chin. J. Trans. CSAE 2003, 19(4):7-12.