Sidescan sonar segmentation using texture descriptors and active contours

IEEE Journal of Oceanic Engineering

Volumn 32, Issue 3, 2007, Pages 744-752

  Lianantonakis, Maria ^a   Petillot, Yvan R ^a  

^a HERIOT WATT UNIVERSITY   (United Kingdom)

Author keywords

Image processing; Seabed classification; Segmentation; Sidescan sonar

Indexed keywords

ALGORITHMS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; OCEAN ENGINEERING;

ACTIVE CONTOURS; SEABED CLASSIFICATION; SIDESCAN SONAR; TEXTURE DESCRIPTORS;

SONAR;

EID: 40449089211     PISSN: 03649059     EISSN: None     Source Type: Journal    
DOI: 10.1109/JOE.2007.893683     Document Type: Article

References (40)

1. T. Chan, B. Sanberg, and L. Vese, "Active contours without edges for vector-valued images," J. Vis. Commun. Image Represent., vol. 11, pp. 130-141, 2000.
2. L. Bjorno, J. Papadakis, P. Papadakis, J. Sageloli, J. Sessarego, S. Sun, and M. Taroudakis, "Identification of seabed data from acoustic reflections: Theory and experiment," Acta Acoustica, vol. 2, pp. 359-374, 1994.
3. D. Sternlicht and C. de Moustier, "Time-dependent seafloor acoustic backscatter (10-100 KHz)," J. Acoust. Soc. Amer., vol. 114, pp. 2709-2721, 2003.
4. B. Zerr, E. Maillard, and D. Gueriot, "Sea-floor classification by neural hybrid system," in Proc. IEEE OCEANS, 1994, pp. 239-243.
5. D. R. Carmichael, L. M. Linnet, S. J. Clarke, and B. R. Calder, "Seabed classification through multi-fractal analysis," Proc. Inst. Electr. Eng. Radar Sonar Navigat., vol. 143, no. 3, pp. 140-148, 1996.
6. M. Mignotte, C. Collet, P. Perez, and P. Bouthemy, "Sonar image segmentation using an unsupervised hierarchical MRF model," IEEE Trans. Image Process., vol. 9, no. 7, pp. 1216-1231, Jul. 2000.
7. S. Reed, Y. Petillot, and J. Bell, "An automatic approach to the detection and extraction of mine features in side-scan sonar," IEEE J. Ocean. Eng., vol. 28, no. 1, pp. 90-105, Jan. 2003.
8. J. M. Bell, M. J. Chantler, and T. Wittig, "Side-scan sonar: A directional filter of seabed texture?," Proc. Inst. Electr. Eng. Radar Sonar Navigat., vol. 146, no. 1, pp. 65-72, 1999.
9. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active contour models," Int. J. Comput. Vis., vol. 1, pp. 321-331, 1988.
10. R. Malladi, J. Sethian, and B. C. Vemuri, "Shape modeling with front propagation: A level set approach," IEEE Trans. Pattern Anal. Mach. Intell., vol. 17, no. 2, pp. 158-175, Feb. 1995.
11. S. Zhu, T. Lee, and A. Yuille, "Region competition: Unifying snakes, region growing and Bayes/MDL for multi-band image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, no. 9, pp. 884-900, Sep. 1996.
12. V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic active contours," Int. J. Comput. Vis., vol. 22, no. 1, pp. 61-79, 1997.
13. A. Yezzi, A. Tsai, and A. Willsky, "A statistical approach to snakes for bimodal and trimodal imagery," in Proc. IEEE Int. Conf. Comput. Vis., 1999, vol. 2, pp. 898-903.
14. T. Chan and L. Vese, "Active contours without edges," IEEE Trans. Image Process., vol. 10, no. 2, pp. 266-277, Feb. 2001.
15. T. Chan and L. Vese, "A level set algorithm for minimizing the Mumford-Shah functional in image processing," in Comput. Soc. Proc. 1st IEEE Workshop Variat. Level Set Methods Comput. Vis., 2001, pp. 161-168.
16. J. Kim, J. Fisher, A. Yezzi, M. Cetin, and A. Willsky, "Non-parametric methods for image segmentation using information theory and curve evolution," in Int. Conf. Image Process., 2002, pp. 797-800.
17. N. Paragios and R. Deriche, "Geodesic active regions: A new framework to deal with frame partition problems in computer vision," J. Vis. Commun. Image Represent., vol. 13, pp. 249-268, 2002.
18. S. Jehan-Besson, M. Barlaud, and G. Aubert, "Deformable regions driven by an Eulerian accurate minimization method for image and video segmentation," Int. J. Comput. Vis., vol. 53, no. 1, pp. 45-70, 2003.
19. S. Osher and J. Sethian, "Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation," J. Comput. Phys., vol. 79, pp. 12-49, 1988.
20. C. Sagiv, N. A. Sochen, and Y. Y. Zeevi, "Integrated active contours for texture segmentation," IEEE Trans. Image Process., vol. 15, no. 6, pp. 1633-1646, Jun. 2006.
21. S. Liapis, E. Silakis, and G. Tziritas, "Color and texture segmentation using wavelet frame analysis, deterministic relaxation, and fast marching algorithms," J. Vis. Commun. Image Represent., vol. 15, no. 1, pp. 1-26, 2004.
22. N. Paragios and R. Deriche, "Geodesic active regions and level set methods for supervised texture segmentation," Int. J. Comput. Vis. vol. 46, no. 3, pp. 223-247, 2002.
23. J.-F. Aujol, G. Aubert, and L. Blanc-Féraud, "Supervised classification for textured images," INRIA, France, Tech. Rep. 4640, 2002.
24. M. Rousson, T. Brox, and R. Deriche, "Active unsupervised texture segmentation on a diffusion based feature space," in Int. Conf. Comput. Vis. Pattern Recognit., 2003, vol. 2, pp. 699-706.
25. B. Sandberg, T. Chan, and L. Vese, "A level-set and Gabor-based active contour algorithm for segmenting textured images," UCLA, Los Angeles, CA, CAM Rep. 02-39, 2002.
26. D. Mumford and J. Shah, "Optimal approximations by piecewise smooth functions and associated variational problems," Commun. Pure Appl. Math., pp. 577-685, 1989.
27. J. Sethian, Level Set Methods and Fast Marching Methods. Cambridge, U.K.: Cambridge Univ. Press, 1999, ch. 6, 7, 16, 17.
28. S. Osher and N. Paragios, Geometric Level Set Methods in Imaging, Vision and Graphics. New York: Springer-Verlag, 2003, ch. 1, 7, 11, 12.
29. S. Osher and R. Fedwick, Level Set Methods and Dynamic Implicit Surfaces. New York: Springer-Verlag, 2003, ch. 3.
30. G. Sapiro, Geometric Partial Differential Equations and Image Analysis. Cambridge, U.K.: Cambridge Univ. Press, 2001, ch. 2.
31. I. Karoui, J.-M Boucher, R. Fablet, and J.-M Agustin, "Multi-scale segmentation of texture sonar images using occurrence statistics," in Proc. Int. Conf. Image Process., 2004, pp. 1691-1694.
32. N. Pican, E. Trucco, M. Ross, D. M. Lane, Y. Petillot, and I. T. Ruiz, "Texture analysis for seabed classification: Co-occurrence matrices versus self-organizing maps," in Proc. IEEE OCEANS, Nice, France, Sep. 1998, pp. 424-428.
33. J. M. Preston, A. C. Christney, S. F. Bloomer, and I. L. Beaudet, "Seabed classification of multi-beam sonar images," in Proc. IEEE OCEANS, 2001, vol. 4, pp. 2616-2623.
34. R. M. Haralick, K. Shanmugam, and I. Dinstein, "Textural features for image classification," IEEE Trans. Syst., Man, Cybern., vol. 3, no. 6, pp. 610-621, 1973.
35. M. Unser, "Sum and difference histograms for texture classification," IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 7, pp. 717-727, Jul. 1989.
36. L. Vese and T. Chan, "A multiple level set framework for image segmentation using the Mumford and Shah model," Int. J. Comput. Vis. vol. 50, no. 3, pp. 271-293, 2002.
37. J.-F. Aujol, G. Aubert, and L. Blanc-Féraud, "Wavelet-based level set evolution for classification of textured images," IEEE Trans. Image Process., vol. 12, no. 12, pp. 1634-1641, Dec. 2003.
38. I. Ayed, A. Mitiche, and Z. Belhadj, "Multiregion level set partitioning of synthetic aperture radar images," IEEE Trans. Image Process., vol. 27, no. 5, pp. 793-800, May 2005.
39. C. Vazquez, A. Mitiche, and I. B. Ayed, "Image segmentation as regularized clustering: A fully global curve evolution method," in Proc. IEEE Int. Conf. Image Process., Oct. 2001, pp. 3467-3470.
40. J. M. Bell and L. M. Linnett, "Simulation and analysis of synthetic side-scan sonar images," Proc. Inst. Electr. Eng. Radar, Sonar Navigat., vol. 144, no. 4, pp. 219-226, 1997.