Developing computer vision algorithm for ripe tomato localization and estimation of the distance from the camera system to the centre of the ripe tomato on the tree
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Jian-jun Y., Han-ping M., Su-yu H., 2009. Segmentation Methods of Fruit Image based on Color Difference. Journal of Communication and Computer 6 (7): 40-45.
Hannan M. W., Burks T. F., Bulanon D. M., 2009. A Machine Vision Algorthm Combining Adaptive Segmentation and Shape Analysis for Orange Fruit Detection. Agricultural Engineering International 11 (1): 1-17.
Hetal N.Patel., Jain R. K., Joshi M. V., 2011. Fruit Detection using Improved Multiple Features based Algorithm. International Journal of Computer Applications 13 (2): 1-5.
Manaf A. Mahammed, Amera I. Melhum, Faris A. Kochery,, 2013. Object Distance Measurement by Stereo Vision. International Journal of Science and Applied Information Technology (IJSAIT) 2 (2): 5-8.
Arman Arefi, Asad Modarres Motlagh, Rahman Farrokhi Teimourlou, 2010. A segmentation algorithm for the automatic recognition of tomato at harvest. Journal of Food, Agriculture & Environment 8 (3&4): 815-819.
Suzuki S., Abe K., 1985. Topological Structural Analysis of Digitized Binary Image by Border Following. Computer Vision, Graphic, and Image Processing 30 (1): 32-46.
Yuen H. K., Princen J., Illingworth J., Kittler J., 1990. Comparative Study of Hough Transform Methods for Circle Finding. Image Vision Computer 8 (1): 71-77.
Luc Vincent, 1993. Morphological Grayscale Reconstruction. In Image Analysis: Applications and Efficient Algorithms. IEEE Transactions on Image Processing 2 (2): 176-201.
Balkenius C., Johansson B., 2007. Finding Colored Objects in a Scene. CiteSeer.
R. Hartley and A. Zisserman, 2000. Multiple View Geometry in Computer Vision. Cambridge University Press, 138-183.
Alain Boucher, IFI 2012. Image processing and Computervision, slide 9 of course, Can Tho University.