Bay, H., A. Ess, T. Tuytelaars, and L. Van Gool. 2008. Speeded-up robust features (SURF). Computer vision and image understanding 110: 346-359.
2. Benson, E., J. Reid, and Q. Zhang. 2003. Machine vision–based guidance system for an agricultural small–grain harvester. Transactions of the ASAE 46: 1255-1264.
3. Bhatti, A. 2011. Global 3D Terrain Maps for Agricultural Applications. Pages 227-242 in Rovira-Mas F, ed. Advances in theory and applications of stereo vision. InTech. Croatia.
4. Bradski, G., and A. Kaehler. 2008. Learning OpenCV: Computer vision with the OpenCV library. O'Reilly Media, Inc. Sebastopol, CA.
5. Brand, C., M. J. Schuster, H. Hirschmüller, and M. Suppa. 2014. Stereo-vision based obstacle mapping for indoor/outdoor SLAM. In IEEE/RSJ International Conference on Intelligent Robots and Systems. Chicago, IL, USA.
6. Canton, J., J. Donaire, and J. Sanchez-Hermosilla. 2012. Stereovision based software to estimate crop parameters in greenhouses. In Infomation Technology, Automation and Precision Farming. International Conference of Agricultural Engineering-CIGR-AgEng: Agriculture and Engineering for a Healthier Life. Valencia, Spain.
7. Civera, J., O. G. Grasa, A. J. Davison, and J. Montiel. 2009. 1-point RANSAC for EKF-based structure from motion. In IEEE/RSJ International Conference on Intelligent Robots and Systems. Louis, USA.
8. Craig, J. J. 2005. Introduction to robotics: mechanics and control. Pearson Prentice Hall. Upper Saddle River, New Jersey, USA.
9. Cyganek, B., and J. P. Siebert. 2009. An Introduction to 3D Computer Vision Techniques and Algorithms. John Wiley & Sons, Ltd. United Kingdom.
10. Hirschmuller, H. 2005. Accurate and efficient stereo processing by semi-global matching and mutual information. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). San Diego, CA, USA.
11. Kise, M., and Q. Zhang. 2008. Development of a stereovision sensing system for 3D crop row structure mapping and tractor guidance. Biosystems Engineering 101: 191-198.
12. Kise, M., Q. Zhang, and F. R. Mas. 2005. A stereovision-based crop row detection method for tractor-automated guidance. Biosystems Engineering 90: 357-367.
13. Kitt, B., A. Geiger, and H. Lategahn. 2010. Visual odometry based on stereo image sequences with RANSAC-based outlier rejection scheme. In Intelligent Vehicles Symposium. University of California, San Diego, CA, USA.
14. Milella, A., B. Nardelli, D. Di Paola, and G. Cicirelli. 2009. Robust Feature Detection and Matching for Vehicle Localization in Uncharted Environments. In Proceedings of the IEEE/RSJ IROS Workshop Planning, Perception and Navigation for Intelligent Vehicles. Saint Louis, USA.
15. Peyman, S. H., A. B. Ziaratgahi, and A. Jafari. 2016. Exploring the possibility of using digital image processing technique to detect diseases of rice leaf. Journal of Agricultural Machinery 6 (1): 69-79. (In Farsi).
16. Rosell, J., and R. Sanz. 2012. A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture 81: 124-141.
17. Rovira-Mas, F., Q. Zhang, and J. Reid. 2005. Creation of three-dimensional crop maps based on aerial stereoimages. Biosystems Engineering 90: 251-259.
18. Rovira-Mas, F., Q. Zhang, and J. F. Reid. 2008. Stereo vision three-dimensional terrain maps for precision agriculture. Computers and Electronics in Agriculture 60: 133-143.
19. So, G. J., S. H. Kim, and J. Y. Kim. 2014. The Extraction of Depth Discontinuities Using Disparity Map for Human Visual Fatigue. International Journal of Computer Theory and Engineering 6: 330-335.
20. Trucco, E., and A. Verri. 1998. Introductory techniques for 3-D computer vision. Prentice Hall. Englewood Cliffs, New Jersey, USA.
21. Xia, C., Y. Li, T. S. Chon, and J. M. Lee. 2009. A stereo vision based method for autonomous spray of pesticides to plant leaves. In Industrial Electronics, ISIE. IEEE International Symposium on. Seoul Olympic Parktel, Seoul, Korea.
22. Yang, L., and N. Noguchi. 2012. Human detection for a robot tractor using omni-directional stereo vision. Computers and Electronics in Agriculture 89: 116-125.
23. Yeh, Y. H. F., T. C. Lai, T. Y. Liu, C. C. Liu, W. C. Chung, and T. T. Lin. 2014. An automated growth measurement system for leafy vegetables. Biosystems Engineering 117: 43-50.
24. Zhang, Z. 1999. Flexible camera calibration by viewing a plane from unknown orientations. In Computer Vision. The Proceedings of the Seventh IEEE International Conference on. Kerkyra, Greece.
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