Abstract
The software is used modularity and qeneric idea, realize target recognition and accurately spraying, it consist of five modules: module of image process, module of identifing the crop from the background of elaphic, module of target recognition and classification of treatment, module of intelligent decision-making and helpness. Image process is made of distortion adjustment,gray strengthen, neighbourhoods average, histogram equalization and median filter; the module of identifing the crop from the background of elaphic is made of division of green strength threshold, division of H hue threshold and segmentation afterwards process and so on; the module of target recognition consist of recognition of fruiter, rice, wheate and target process and area calculating, the module of recognition of fruiter include centre recognition function; the module of intelligent decision-making include information target transmited. The system has fault-tolerant function and automatically judges the input of image or not, automatically detects input of camera and terminal setting, connection situation of singlechip, creating executable file, breaking away from VC++ then direct running. Limiting surface of software system is friendly, simple clear and satisfy the real-time processing the request.
Chapter PDF
Similar content being viewed by others
References
Won, S.L.: Robotic weed control system for tomatoes using machine vision system and precision chemical application. An ASAE Meeting Presentation 3093, 1–14 (1997)
Sheng, L.M.: Corn seedling weed identification in machine vision research Yang Ling: Northwest A&F University, 3 (2002)
Paice, M.E., Miller, P.C.H., Bodle, J.D.: An experimental sprayer for the spatially selective application of herbicides. J. Agric-Eng. Res. 60(2), 107–116 (1995)
Wei, Z.: Research on the Technology of PWM Variable Sprayer, p. 4. Jiangsu University, Zhen Jiang (2006)
Kenzel, M.: United State Patent (December 1, 1998)
Maocheng, Z., Jiaqiang, Z.: Tree crown recognition and precision toward-target pesticide application. Transactions of The Chinese Society of Agricultural Engineering (6), 150–153 (2003)
Qiu, B., Li, H., Wu, C.: On variable-rate spraying equipment and its key technology. Journal of Jiangsu University (National Science Edition) 98, 97–98 (2004)
Feng, G.Y.: Indoor Pesticide Smart-Targeting Application Simulation System Based on Machine Vision Master thesis]Nanjing Forestry University (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 IFIP International Federation for Information Processing
About this paper
Cite this paper
Shi, Y., Zhang, C., Li, M., Yuan, H. (2011). Target Recognition of Software Research about Machine System of Accurately Spraying. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18354-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-18354-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18353-9
Online ISBN: 978-3-642-18354-6
eBook Packages: Computer ScienceComputer Science (R0)