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標題: 運用聚類技術進行形貌影像分割
Range Image Segmentation Using Clustering Techniques
作者: 陳瑩聰
Chen, Ying-Tsung
關鍵字: 形貌影像;range image;影像分割;表面型態標記;RANSAC;幾何元件擬合;分層聚類;image segmentation;surface curvature;RANSAC;3-D object description;hierarchical clustering
出版社: 機械工程學系所
引用: [1] O. D. Faugeras , M. Herbert , E. Pauchon , “Segmentation of range image into planar and quadratic patches”, Proc. IEEE Conf. Computer vision and pattern Recognition, pp. 8-13, June 1983. [2] M. Oshima , Y. Shirai ,“Object recognition using three-dimensional information”, IEEE Trans. Pattern Anal. Machine Intell. , vol. PAMI-5 , pp.353-361, July 1983. [3] P. J. Besl , R. C. Jain, “Invariant surface characteristics for 3D object recognition in range image ” , Computer Vision Graphic and image processing , 33, pp. 33-80 , 1986. [4] P. J. Besl , R. C. Jain, “Segmentation through variable-order surface fitting” , Proc. IEEE Conf. Computer vision and Pattern Recognition ,vol. 10 ,No.2 , March 1988. [5] N. Yakoya , M. D. Levine, “Range Image Segmentation Based on Differential Geometry: A Hybrid Approach”, IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 11,No.6,June 1989. [6] C. Zhao , D. Zhao , Y. Chen , “Simplified Gaussian and Mean curvatures to range image segmentation ” , IEEE Pro. Of ICPR , 1996. [7] X. Jiang , H. Burke , “Edge detection in range image based on scan line approximation ” , Computer vision and image understanding , vol.73,No.2, pp. 183-199, February 1999. [8] A. D. Sappa , M. Devy , “Fast range image segmentation by an edge detection strategy” , Proc. IEEE Conf. 3-D Digital Imaging and Modeling, pp. 292-299 , 2001. [9] A.K. Jain , M.N. Murty , P.J. Flynn, “Data Clustering: A Review” , ACM Computing Surveys, Vol. 31, No. 3, September 1999. [10] E. Cohen , R. F. Riesenfeld , G . Elber , Geometric Modeling with Splines , A K Peter , pp. 341-432 , 2001. [11] P. J. Besl , R. C. Jain , “Segmentation Through Variable-Order Surface Fitting”, IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 10,No.2, pp. 167-192 , June 1988
在影像視覺中,從一張含有三維資訊的影像中直接獲得有用的資訊有所困難,因此形貌影像分割(Range Image segmentation)為一個很重要的初步處裡,將原始影像中的物件表面分割為基本的幾何元件,幾何元件包含平面、球面、圓柱面以及圓錐面。一個機械元件往往含有許多的不同的幾何元件且若直接一次分析整張影像全部的像素點容易造成運算時間過長,因此在本文使用分層聚類的觀念,先將影像分割為小的區塊,再由這些區塊去找尋出各元件。

In computer vision, get a useful information directly from the one containing the image of the three-dimensional information has been difficult, the range image segmentation is a very important initial at the object surface in the original image is dividedbasic geometric elements and geometric elements with plane, spherical, cylindrical and conical surface.
A mechanical components often contain many different geometric components and if the direct analysis to the image all the pixels likely to cause long computation time, so in this paper,we use of the hierarchical clustering , the first image is divided into small blocksby block to find the components.
In this paper,the first step use sign the the Gaussian curvature and mean curvature of the surface morphology,than we use RANSAC algorithm to identify all the surface elements from the sign image.
其他識別: U0005-0708201214451300
Appears in Collections:機械工程學系所

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