Orientation space filtering for multiple orientation line segmentation

The goal of this paper is to present appropriate line segmentation for intersections (X-junctions) and branches (T-junctions). In the local regions of intersections and branches, multiple orientations occur. A novel representation called "orientation space" is proposed, which is derived by adding the orientation axis to the abscissa and the ordinate of the image. The orientation space representation is constructed by treating the orientation parameter, to which Gabor filters can be tuned, as a continuous variable. The problem of multiple orientation line segmentation is dealt with by thresholding 3D images of the orientation space and then detecting the connected components therein. In this way, X-junctions and T-junctions are able to be separated effectively. Experimental results are presented using synthesized and real biomedical images. In particular, overlapping vessels in an x-ray coronary angiogram were well segmented by orientation space filtering.

[1]  David J. Kriegman,et al.  Structure and Motion from Line Segments in Multiple Images , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  G. Granlund In search of a general picture processing operator , 1978 .

[3]  Andrew P. Witkin,et al.  Analyzing Oriented Patterns , 1985, IJCAI.

[4]  Kuo-Chin Fan,et al.  A robust algorithm for separation of Chinese characters from line drawings , 1996, Image Vis. Comput..

[5]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[6]  Guido Gerig,et al.  Multiscale detection of curvilinear structures in 2-D and 3-D image data , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  Tony Lindeberg,et al.  Edge Detection and Ridge Detection with Automatic Scale Selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Jitendra Malik,et al.  Detecting and localizing edges composed of steps, peaks and roofs , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[9]  Carsten Steger,et al.  An Unbiased Detector of Curvilinear Structures , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  J. Daugman Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[11]  Gerald Sommer,et al.  Junction classification by multiple orientation detection , 1994, ECCV.

[12]  Andrew P. Witkin,et al.  Uniqueness of the Gaussian Kernel for Scale-Space Filtering , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Pietro Perona Steerable-scalable kernels for edge detection and junction analysis , 1992, Image Vis. Comput..

[14]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Steven W. Zucker,et al.  Computing Contour Closure , 1996, ECCV.

[16]  Josiane Zerubia,et al.  New Prospects in Line Detection by Dynamic Programming , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Michael Lindenbaum,et al.  Curve Segmentation Under Partial Occlusion , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Zhengyou Zhang Estimating Motion and Structure from Correspondences of Line Segments between Two Perspective Images , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Alan L. Yuille,et al.  Scaling Theorems for Zero Crossings , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Brian G. Schunck,et al.  Image Flow Segmentation and Estimation by Constraint Line Clustering , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Ingemar J. Cox,et al.  A Bayesian Multiple Hypothesis Approach to Contour Grouping , 1992, ECCV.

[22]  Tony Lindeberg,et al.  Scale-Space for Discrete Signals , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Bidyut Baran Chaudhuri,et al.  Detection of linear features in satellite imagery using robust estimation , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[24]  P. Perona,et al.  Detecting and localizing edges composed of steps , 1990 .

[25]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[26]  Steven W. Zucker,et al.  Trace Inference, Curvature Consistency, and Curve Detection , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Guido Gerig,et al.  3D Multi-scale line filter for segmentation and visualization of curvilinear structures in medical images , 1997, CVRMed.

[28]  R.A. Zoroofi,et al.  Automatic extraction and measurement of leukocyte motion in microvessels using spatiotemporal image analysis , 1997, IEEE Transactions on Biomedical Engineering.

[29]  Steven W. Zucker,et al.  Early orientation selection: Tangent fields and the dimensionality of their support , 1985, Comput. Vis. Graph. Image Process..

[30]  Yoshinobu Sato,et al.  Measuring Microcirculation Using Spatiotemporal Image Analysis , 1995, CVRMed.

[31]  Jose A. Ventura,et al.  Segmentation of planar curves into circular arcs and line segments , 1996, Image Vis. Comput..

[32]  Rüdiger von der Heydt,et al.  Detection of General Edges and Keypoints , 1992, ECCV.