Affine invariant detection of perceptually parallel 3D planar curves

doi:10.1016/S0031-3203(99)00172-7

Pattern Recognition

Volume 33, Issue 11, November 2000, Pages 1909-1918

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Abstract

The problem of parallelism detection between two curves has been formulated in this paper as a line detection problem within an affine-invariant local similarity matrix computed for the two curves. Each element of this matrix gives an affine invariant measure of local parallelism for any pair of curve segments along the two curves. This approach enables the detection of a pair of parallel 3D planar curves as well as parallel 2D curves under general affine transform. Two descriptors were also used here to provide a multi-resolution representation of a curve. Since these two descriptors provide sufficient local and semi-local shape information at every feature point on the curves, the process of detecting parallelism is thus robust against both noise and deformations. Moreover, the proposed technique allows all significant pairs of parallel segments within any two curves in the scene to be detected. Experiments on detecting randomly affine-transformed curves, which are obtained from natural images or artificially generated images, have demonstrated the effectiveness of the technique.

Keywords

Parallelism detection

Local invariants

Semi-local invariants

Affine invariant

Shape matching

Symmetry detection

3D parallel curves

Hand-written digit recognition

Cited by (0)

About the Author—DINGGANG SHEN received his B.S., M.S. and Ph.D. degrees in Electronics Engineering from Shanghai JiaoTong University (SJTU) in 1990, 1992 and 1995, respectively. He worked as Research Assistant in the Department of Computer Science at the Hong Kong University of Science & Technology from December 1994 to June 1995. From September 1995 to February 1996, he was a Lecturer of Communication Engineering at Shanghai JiaoTong University. He was a Research Fellow in the Department of Computer Science at City University of Hong Kong, from February 1996 to August 1997. From June 1997 to February 1999, he worked first as Post-Doctoral Fellow and then as Research Fellow in the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore. Since January 1999, he worked as Postdoctoral Research Fellow in School of Medicine at Johns Hopkins University, doing medical imaging. His research interests are in the areas of computer vision, pattern recognition, image processing, neural network and image indexing and retrieval.

About the Author—HORACE H.S. IP received his B.Sc. (First Class Honours) degree in Applied Physics and Ph.D. degree in Image Processing from University College London, United Kingdom, in 1980 and 1983, respectively. Presently, he is the Professor and Head of the Computer Science Department and also heads the Image Computing Research Group, at City University of Hong Kong. His research interests include image processing and analysis, pattern recognition, hypermedia computing systems and computer graphics. Prof. Ip is a member of the Editorial Boards for Pattern Recognition (Elsevier), the International Journal of Multimedia Tools and Applications (Kluwer Academic), and the Chinese Journal of CAD and Computer Graphics (The Chinese Academy of Science) and a guest editor of the international journal of Real-Time Imaging (Academic Press).

Prof. Ip serves on the IAPR Governing Board and co-chairs its Technical Committee on Multimedia Systems. He was the Chairman of the IEEE (HK) Computer chapter, and the Founding President of the Hong Kong Society for Multimedia and Image Computing. He has published over 80 papers in international journals and conference proceedings.

About the Author—EAM KHWANG TEOH received his B.E. and M.E. degrees in Electrical Engineering from the University of Auckland, New Zealand in 1980 and 1982, respectively, and the Ph.D. degree in Electrical & Computer Engineering from the University of Newcastle, New South Wales in 1986. Presently, he is a Vice-Dean and an Associate Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He is a co-inventor of an Australian Patent on An Adaptive Thickness Controller for a Rolling Mill. His current research interests are in the field of Computer Vision and Pattern Recognition, Intelligent Systems, Robotics and Industrial Automation. He has published more than 150 journal and conference papers in these areas.