Detection of Control Points for Warping Map Images

Abstract This paper presents a method for automatically detecting line intersections. The underlying application is to detect the road junction locations in map images to serve as control points for warping the images. This method applies a local energy detector to the two dimensions of an image for detecting edges. Also, a new way of using the Hough transform is proposed to facilitate the detection of the appropriate intersection points. This algorithm is integrated with a real application software system, the CRIM Image Mining Environment (CIIvIE), which is being developed for industrial applications.

[1]  A. Rosenfeld,et al.  Edge and Curve Detection for Visual Scene Analysis , 1971, IEEE Transactions on Computers.

[2]  Ming Zhang.  On the discretization of parameter domain in Hough transformation , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  D. Burr,et al.  Evidence for edge and bar detectors in human vision , 1989, Vision Research.

[5]  Christian Ronse,et al.  On Idempotence and Related Requirements in Edge Detection , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Heinrich Müller,et al.  Image warping with scattered data interpolation , 1995, IEEE Computer Graphics and Applications.

[7]  P. Sankar,et al.  A parallel procedure for the detection of dominant points on a digital curve , 1978 .

[8]  Svetha Venkatesh,et al.  Edge detection is a projection , 1989, Pattern Recognit. Lett..

[9]  D. Burr,et al.  Feature detection in human vision: a phase-dependent energy model , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[10]  Azriel Rosenfeld,et al.  Edge and Curve Detection: Further Experiments , 1972, IEEE Transactions on Computers.

[11]  Ying Li,et al.  A knowledge-based image understanding environment for document processing , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[12]  Rae-Hong Park,et al.  Edge-preserving artifact-free smoothing with image pyramids , 1991, Pattern Recognit. Lett..

[13]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[14]  Fredrik Bergholm,et al.  Edge Focusing , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Axel Korn,et al.  Toward a Symbolic Representation of Intensity Changes in Images , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Yehoshua Y. Zeevi,et al.  Pyramidal Edge Detection And Image Representation , 1988, Other Conferences.

[17]  Rae-Hong Park,et al.  Multiresolution edge detection techniques , 1995, Pattern Recognit..

[18]  Roland T. Chin,et al.  On the Detection of Dominant Points on Digital Curves , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Larry S. Davis,et al.  A Corner-Finding Algorithm for Chain-Coded Curves , 1977, IEEE Transactions on Computers.

[20]  Azriel Rosenfeld,et al.  Angle Detection on Digital Curves , 1973, IEEE Transactions on Computers.

[21]  Robyn A. Owens,et al.  Feature detection from local energy , 1987, Pattern Recognit. Lett..

[22]  A. Ardeshir Goshtasby,et al.  Piecewise cubic mapping functions for image registration , 1987, Pattern Recognit..

[23]  Ying Li,et al.  A fast warping algorithm for correcting local distortions in binary images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[24]  James C. Bezdek,et al.  Curvature and Tangential Deflection of Discrete Arcs: A Theory Based on the Commutator of Scatter Matrix Pairs and Its Application to Vertex Detection in Planar Shape Data , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Azriel Rosenfeld,et al.  An Improved Method of Angle Detection on Digital Curves , 1975, IEEE Transactions on Computers.