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A study of a multi-view ship recognition prototype system
|關鍵字:||Gradient Vector Flow;動態梯度向量流;Ship Recognition;Fourier Descriptor;船艦辨識;傅立葉描述子||出版社:||電機工程學系所||引用:|| A. Pope and D. Lowe, “Learning object recognition models from images,” ICCV, pp. 296-301, 1993.  I. Weiss and M. Ray, “Model-based recognition of 3D objects from single images,” PAMI, vol.23, no.2, pp. 116-128, 2001.  P. Flynn and A. Jain, “BONSAI: 3D object recognition using constrained search,” PAMI, vol.13, no.10, pp. 1066-1075, 1991.  F. Leymarie and B.B. Kimia, “The shock scaffold for representing 3D shapes,” Proc. of the Int. Workshop on Visual Form, Springer: Capri, Italy, pp. 216-228, 2001.  P. J. Besl and R. C. Jain, “Three-dimensional object recognition,”Comput. Surveys, vol. 1, no. 1, pp. 11-23, 1985.  R. T. Chin and C. R. Dyer, “Model-based recognition in robot vision,”ACM Computi. Surveys, vol. 18, no. 1, 1986.  J. T. Feddema, C. S. G. Lee, and O. R. Mitchell, “Weighted selection of image features for resolved rate visual feedback control,” IEEE Trans.Robot. Automat., vol. 7, pp. 31-47, Feb. 1991.  L. E.Weiss, A. C. Sanderson, and C. P. Neuman, “Dynamic sensor-based control of robots with visual feedback,” IEEE Trans. Robot. Automat.,vol. RA-3, no. 5, pp. 404-417, Oct. 1987.  H. Murase and S. K. Nayar, “Visual learning and recognition of 3-d objects from appearance,” Int. J. Comput. Vision, vol. 14, no. 1, pp. 5-24, 1995.  S. K. Nayar, S. A. Nene, and H. Murase, “Subspace methods for robot vision,” IEEE Trans. Robot. Automat., vol. 12, p. 750, Oct. 1996.  T. Poggio and S. Edelman, “A network that learns to recognize 3D objects,” Nature, vol. 343, pp. 263-266, 1990.  M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cognitive Neurosci., vol. 3, no. 1, pp. 71-86, 1991.  M. A. Turk and A. P. Pentland, “Face recognition using eigenfaces,” Proc. IEEE Computer Society Conf. Computer Vision Pattern Recognition, Maui, HI, 1991, pp. 586-591.  J.Weng, N. Ahuja, and T. S. Huang, “Learning recognition and segmentation of 3-D objects from 2-D images,” Proc.4th Int. Conf. Computer Vision, Berlin, Germany, May 1993, pp. 121-128.  L. Sirovich and M. Kirby, “Low-dimensional procedure for the characterization of human faces,” J. Opt. Soc. Amer., vol. 4, no. 3, pp. 519-524,Mar. 1987.  J. J Koenderink, and A. van Doorn, “The internal representation of solid shape with respect to vision”, Biological Cybernetics , vol. 32, pp. 211-216, 1979.  M. Kass, A. Witkin, and D. Terzopoulos, “Snake: active contour models,” Int. Journal of Computer Vision, pp. 321-331,1988.  C. Y. Xu and J. L. Prince, “Snakes, shapes, and gradient vector flow,” IEEE Trans. Image Processing, vol. 7, no. 3, pp. 359-369, 1998.  J. F. Canny, “A computational approach to edge detection,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, 1986.||摘要:||
在電腦視覺之研發領域，三維物體辨識(3D object recognition)是相當重要之一項技術，使電腦能像人類一樣只單純的看到一個三維物體的某一個方向的影像，就能判斷出那是一個什麼東西。如果可以的話，我們便能將其應用在國防科技上例如:移動目標物之辨識，敵我戰車之識別，海防監視應用系統等，那麼我們就擁有快速反應和全天候監控的能力。
In the field of research and development of the vision of the computer, 3D objects recognition is quite important a technology. It make computer like mankind to see a certain direction of 3D objects then to recognize a 3D object. If all right, we can apply it in military defense applications for example: Moving target recognition、the identification of enemy/non-enemy tanks、the coast defense surveillance system etc. Then we have a fast reaction and all-weather ability to control.
The purpose of ship recognition system is that we can have a technology to research and develop for gathering contour of ship in the natural sea area. We can develop a set of ship recognition system which is reliable and fast to cooperate with a good ship characteristic database. We have proposed in this paper a system for ship recognition. This system uses gradient vector flow (GVF ) to gather the contour of ship image first and calculate out its geometry characteristic value by using this contour and fourier descriptor. We use these characteristic values to do rough and detail recognition separately. In this system we use Matlab software to set up graphic user interface and user can through this interface carry out recognition of ship by the way of interaction.
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