Identifying salient circular arcs on curves

Abstract This paper addresses the problem of identifying perceptually significant segments on general planar curvilinear contours. Lacking a formal definition for what constitutes perceptual salience, we develop subjective criteria for evaluating candidate segmentations and formulate corresponding objective measures. An algorithm following these criteria delivers segments with following properties: (1) each segment is well approximated by a circular arc; (2) each pair of segments describe different sections of the contour; and (3) the curve either terminates or changes in orientation and/ or curvature beyond each end of every segment. The result is a description of the contour at multiple scales in terms of circular arcs that may overlap one another.

[1]  Steven W. Zucker,et al.  The Organization Of Curve Detection: Coarse Tangent Fields And Fine Spline Coverings , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[2]  Eric Saund,et al.  Putting Knowledge Into a Visual Shape Representation , 1992, Artif. Intell..

[3]  Maureen Stone,et al.  Curve-fitting with piecewise parametric cubics , 1983, SIGGRAPH.

[4]  David J. Farber,et al.  A Parallel Mechanism for Detecting Curves in Pictures , 1975, IEEE Transactions on Computers.

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

[6]  Shimon Ullman,et al.  Structural Saliency: The Detection Of Globally Salient Structures using A Locally Connected Network , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[7]  Robert C. Bolles,et al.  Locating Partially Visible Objects: The Local Feature Focus Method , 1980, AAAI.

[8]  Thomas L. Hemminger,et al.  Polygonal representation: A maximum likelihood approach , 1990, Comput. Vis. Graph. Image Process..

[9]  John K. Tsotsos,et al.  Recognizing planar curves using curvature-tuned smoothing , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[10]  Theodosios Pavlidis,et al.  Segmentation of Plane Curves , 1974, IEEE Transactions on Computers.

[11]  Eugene Wong,et al.  Approximating parametric curves with strip trees using affine arithmetic , 2002, Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing.

[12]  R. Bolles,et al.  Recognizing and Locating Partially Visible Objects: The Local-Feature-Focus Method , 1982 .

[13]  David G. Lowe,et al.  Perceptual Organization and Visual Recognition , 2012 .

[14]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

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

[16]  Steven W. Zucker,et al.  The Organization Of Curve Detection: Coarse Tangent Fields And Fine Spline Coverings , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[17]  Yee-Hong Yang,et al.  Dynamic strip algorithm in curve fitting , 1990, Comput. Vis. Graph. Image Process..

[18]  Gérard G. Medioni,et al.  Corner detection and curve representation using cubic B-splines , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[19]  G. Medioni,et al.  Corner detection and curve representation using cubic B-splines , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[20]  Hiroshi Imai,et al.  Computational-geometric methods for polygonal approximations of a curve , 1986, Comput. Vis. Graph. Image Process..

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

[22]  F. Bookstein.  Fitting conic sections to scattered data , 1979 .

[23]  Yiu-Tong Chan,et al.  A simple approach for the estimation of circular arc center and its radius , 1989, Comput. Vis. Graph. Image Process..

[24]  Jack Sklansky,et al.  On the Hough Technique for Curve Detection , 1978, IEEE Transactions on Computers.

[25]  Jitendra Malik,et al.  Detecting Curvilinear Structure in Images , 1991 .

[26]  Donald D. Hoffman,et al.  Parts of recognition , 1984, Cognition.

[27]  Michael Shneier.  Extracting linear features from images using pyramids , 1980 .

[28]  Richard S. Weiss,et al.  Perceptual Grouping Of Curved Lines , 1989, Other Conferences.

[29]  Ramakant Nevatia,et al.  Segmentation and description based on perceptual organization , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[30]  Robert C. Bolles,et al.  Perceptual Organization and Curve Partitioning , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  Michael Brady,et al.  The Curvature Primal Sketch , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[32]  Pnvid H Ivl,et al.  A Representation for Image Curves , 1984, AAAI.

[33]  A. Witkin,et al.  On the Role of Structure in Vision , 1983 .

[34]  Hiroshi Aoyama,et al.  A piecewise linear approximation method preserving visual feature points of original figures , 1991, CVGIP Graph. Model. Image Process..

[35]  W. Eric L. Grimson.  On the Recognition of Curved Objects , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[36]  Charles M. Williams,et al.  An Efficient Algorithm for the Piecewise Linear Approximation of Planar Curves , 1978 .

[37]  W. A. Perkins,et al.  A Model-Based Vision System for Industrial Parts , 1978, IEEE Transactions on Computers.