Salient closed boundary extraction with ratio contour

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 27, Issue 4, 2005, Pages 546-561

  Wang, Song ^a   Kubota, Toshiro ^a   Siskind, Jeffrey Mark ^b   Wang, Jun ^a  

^a University of South Carolina   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

Boundary detection; Edge detection; Graph models; Image segmentation; Perceptual organization

Indexed keywords

ALGORITHMS; EDGE DETECTION; GRAPH THEORY; IMAGE SEGMENTATION; MATHEMATICAL MODELS; OPTIMIZATION; POLYNOMIALS; SPECTRUM ANALYSIS;

BOUNDARY DETECTION; GRAPH MODELS; PERCEPTUAL ORGANIZATION;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 17144381306     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2005.84     Document Type: Article

References (68)

1. R.K. Ahuja, T.L. Magnanti, and J.B. Orlin, Network Flows: Theory, Algorithms, & Applications. Prentice Hall, 1993.
2. T. Alter and R. Basri, "Extracting Salient Contours from Images: An Analysis of the Saliency Network," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 13-20, 1996.
3. A.A. Amini, T.E. Weymouth, and R.C. Jain, "Using Dynamic Programming for Solving Variational Problems in Vision," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 9, pp. 855-867, 1990.
4. A. Amir and M. Lindenbaum, "A Generic Grouping Algorithm and Its Quantitative Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 2, pp. 168-185, Feb. 1998.
5. A. Barbu and S.C. Zhu, "Graph Partition by Swendsen-Wang Cuts," Proc. Int'l Conf. Computer Vision, 2003.
6. K. Bowyer, C. Kranenburg, and S. Dougherty, "Edge Detector Evaluation Using Empirical ROC Curves," Computer Vision and Image Understanding vol. 84, no. 10, pp. 77-103, 2001.
7. J. Canny, "A Computational Approach to Edge Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, 1986.
8. V. Casselles, F. Catte, T. Coll, and F. Dibos, "A Geometric Model for Active Contours," Numerische Mathematik, vol. 66, no. 1, pp. 1-31, 1993.
9. L.D. Cohen and I. Cohen, "A Finite Element Method Applied to New Active Contour Models and 3D Reconstruction from Cross Sections," Proc. Int'l Conf. Computer Vision, pp. 587-591, 1990.
10. W. Cook and A. Rohe, "Computing Minimum-Weight Perfect Matchings," http://www.or.unibonn.de/home/rohe/matching.html, Aug. 1998.
11. T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham, "Active Shape Models--Their Training and Application," Computer Vision and Image Understanding, vol. 61, no. 1, pp. 38-59, 1995.
12. T.H. Cormen, C.E. Leiserson, and R.L. Rivest, Introduction to Algorithms. Cambridge: MIT Press and New York: McGraw Hill, 1990.
13. I. Cox, S.B. Rao, and Y. Zhong, "Ratio Regions: A Technique for Image Segmentation," Proc. Int'l Conf. Pattern Recognition, pp. 557-564, 1996.
14. E. Dijkstra, "Note on Two Problems ba Connection with Graphs," Nurnerische Mathematik, vol. 1, pp. 269-271, 1959.
15. J. Edmonds, "Path, Trees, and Flowers," Canadian J. Math., vol. 17, pp. 449-467, 1965.
16. J. Elder and S. Zucker, "Computing Contour Closure," Proc. European Conf. Computer Vision, pp. 399-412, 1996.
17. H.N. Gabow, "A Scaling Algorithm for Weighted Matching on General Graphs," Proc. 26th Ann. Symp. Foundations of Computer Science, pp. 90-100, 1985.
18. M. Galun, E. Sharon, R. Basri, and A. Brandt, "Texture Segmentation by Multiscale Aggregation of Filter Responses and Shape Elements," Proc. Int'l Conf. Computer Vision, 2003.
19. Y. Gdalyahu, D. Weinshall, and M. Werman, "Stochastic Image Segmentation by Typical Cuts," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 596-601, 1999.
20. S. Geman and D. Geman, "Stochastic Relaxation, Gibbs Distribution, and the Bayesian Restoration of Images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 6, no. 6, pp. 721-741, 1984.
21. G. Guy and G. Medioni, "Inferring Global Perceptual Contours from Local Features," Int'l J. Computer Vision, vol. 20, no. 1, pp. 113-133, 1996.
22. X. Han, C. Xu, and J.L. Prince, "A Topology Preserving Deformable Model Using Level Set," Proc. IEEE Conf Computer Vision and Pattern Recognition, vol. 2, pp. 765-770, 2001.
23. P. Hart, N. Nilsson, and B. Raphael, "A Formal Basis for the Heuristic Determination of Minimum-Cost Path," IEEE Trans. Systems, Man, and Cybernetics, vol. 4, pp. 100-107, 1968.
24. M.D. Heath, S. Sarkar, T. Sanocki, and K.W. Bowyer, "A Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms," IEEE Trans. Pattern Analysis and Machine Intelligence vol. 19, no. 12, pp. 1338-1359, Dec. 1997.
25. L. Herault and R. Horaud, "Figure-Ground Discrimination: A Combinatorial Optimization Approach," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, pp. 899-914, 1993.
26. L.A. Iverson and S.W. Zuker, "Logic/Linear Operators for Image Curves," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 10, pp. 982-996, Oct. 1995.
27. D. Jacobs, "Robust and Efficient Detection of Convex Groups," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 1, pp. 23-37, Jan. 1996.
28. A.K. Jain, Y. Zhong, and S. Lakshmanan, "Object Matching Using Deformable Templates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 3, pp. 267-278, Mar. 1996.
29. I.H. Jermyn and H. Ishikawa, "Globally Optimal Regions and Boundaries as Minimum Ratio Cycles," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 10, pp. 1075-1088, Oct. 2001.
30. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active Contour Models," Int'l J. Computer Vision, vol. 1, no. 4, pp. 321-331, 1988.
31. B.B. Kimia, I. Frankel, and A.-M. Popescu, "Euler Spiral for Shape Completion," Int'l J. Computer Vision, vol. 54, pp. 157-180, 2003,
32. S. Konishi, A.L. Yuille, J.M. Coughlan, and S.C. Zhu, "Statistical Edge Detection: Learning and Evaluating Edge Cues," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 1, pp. 57-74, Jan. 2003.
33. I. Kovacs and B. Julesz, "A Closed Curve is Much More than ah Incomplete One: Effect of Closure in Figure-Ground Segmentation," Proc. Nat'l Academy of Science USA, vol. 90, pp. 7495-7497, 1993.
34. T. Kubota, "Contextual and Non-Combinatorial Approach to Feature Extraction," Proc. Int'l Workshop Energy Minimization Methods in Computer Vision and Pattern Recognition, 2003.
35. T.-S. Lee, D. Mumford, and A. Yuille, "Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model," Proc. European Conf. Computer Vision, pp. 165-183, 1992.
36. M.E. Leventon, E.L. Grimson, and O. Faugeras, "Statistical Shape Influence in Geodesic Active Contours," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 316-323, 2000.
37. S. Mahamud, L.R. Williams, K.K. Thornber, and K. Xu, "Segmentation of Multiple Salient Closed Contours from Real Images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 4, pp. 433444, Apr. 2003.
38. D. Mumford,"Bayesian Rationale for the Variational Formulation," Geometry-Driven Diffusion in Computer Vision, B.M.H. Romeny, ed., pp. 135-143, Kluwer, 1994.
39. M. Nitzberg, D. Mumford, and T. Shiota, "Filtering, Segmentation and Depth," Lecture Notes in Computer Science, vol. 662, New York: Springer-Verlag, 1993.
40. P. Perona, "A Factorization Approach to Grouping," Proc. European Conf. Computer Vision, pp. 655-670, 1998.
41. J.M. Prewitt, "Object Enhancement and Extraction," Picture Processing and Psychopictorics, B. Lipkin and A. Rosenfeld, eds., pp. 75-149, New York: Academic Press, 1970.
42. S. Raman, S. Sarkar, and K. Boyer, "Hypothesizing Structures in Edge-Focused Cerebral Magnetic Resonance Images Using Graph-Theoretic Cycle Enumeration," Computer Vision, Graphics, and Image Processing vol. 57, no. 1, pp. 81-98, 1993.
43. K.R. Rao and J. Ben-Arie, "Optimal Edge Detection Using Expansion Matching and Restoration," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 12, pp. 1169-1182, Dec. 1994.
44. X. Ren and J. Malik, "A Probabilistic Multi-Scale Model for Contour Completion Based on Image Statistics," Proc. European Conf. Computer Vision, vol. 1, pp. 312-327, 2002.
45. L.G. Roberts, "Machine Perception of Three-Dimensional Solids," Optical and Electro-Optical Information Processing, J.T. Tippett, ed., pp. 159-197, Cambridge, Mass.: Massachusetts Inst. of Technology Press, 1965.
46. B.M.H. Romeny, Geometry-Driven Diffusion in Computer Vision. Dordrecht & Boston: Kluwer Academic Publishers, 1994.
47. D. Rueckert and P. Burger, "Geometrically Deformable Templates for Shape-Based Segmentation and Tracking in Cardiac MR Image," Proc. Int'l Workshop Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 83-98, 1997.
48. S. Sarkar and K. Boyer, "Quantitative Measures of Change Based on Feature Organization: Eigenvalues and Eigenvectors," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 478-483, 1996.
49. S. Sarkar and P. Soundararajan, "Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning Automata," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 5, pp. 504-525, May 2000.
50. E. Sharon, A. Brandt, and R. Basri, "Completion Energies and Scale," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1117-1131, Oct. 2000.
51. E. Sharon, A. Brandt, and R. Basti, "Fast Multiscale Image Segmentation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 70-77, 2000.
52. E. Sharon, A. Brandt, and R. Basti, "Segmentation and Boundary Detection Using Multiscale Intensity Measurements," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 469-476, 2001.
53. A. Shashua and S. Ullman, "Structural Saliency: The Detection of Globally Salient Structures Using a Locally Connected Network," Proc. Int'l Conf. Computer Vision, pp. 321-327, 1988.
54. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888-905, Aug. 2000.
55. I.E. Sobel, "Camera Models and Machine Perception," PhD dissertation, Stanford Univ., Stanford, Calif., 1970.
56. P. Soundararajan and S. Sarkar, "Ah In-Depth Study of Graph Partitioning Measures for Perceptual Organization," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 642-660, June 2003.
57. L.H. Staib and J.S. Ducan, "Boundary Finding with Parametrically Deformable Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 11, pp. 1061-1075, Nov. 1992.
58. K.K. Thornber and L.R. Williams, "Analytic Solution of Stochastic Completion Fields," Biological Cybernetics, vol. 75, pp. 141-151,1996.
59. O. Veksler, "Image Segmentation by Nested Cuts," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 339-344, 2000.
60. S. Wang, T. Kubota, and J.M. Siskind, "Salient Boundary Detection Using Ratio Contour," Proc. Neural Information Processing Systems Conf. pp. 1571-1578, 2003.
61. S. Wang and J.M. Siskind, "Image Segmentation with Ratio Cut," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 675-690, June 2003.
62. S. Wang, J. Wang, and T. Kubota, "From Fragments to Salient Closed Boundaries: An In-Depth Study," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. I, pp. 291-298, 2004.
63. D.. Williams and M. Shah, "A Fast Algorithm for Active Contours," Proc. Int'l Conf. Computer Vision, pp. 592-595, 1990.
64. L. Williams and D. Jacobs, "Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and Salience," Neural Computation vol. 9, pp. 849-870, 1997.
65. L. Williams and K.K. Thornber, "A Comparison Measures for Detecting Natural Shapes in Cluttered Background," Int'l J. Computer Vision vol. 34, nos. 2/3, pp. 81-96, 2000.
66. Z. Wu and R. Leahy, "Ah Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1101-1113, Nov. 1993.
67. C. Xu and J.L. Prince, "Snakes, Shapes, and Gradient Vector Flow," IEEE Trans. Image Processing, vol. 7, no. 3, pp. 359-369,1998.
68. S.C. Zhu and A. Yuille, "Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multi-Band Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 9, pp. 884-900, Sept. 1996.