Textured image segmentation using active contours

Communications in Computer and Information Science

Volumn 68 CCIS, Issue , 2010, Pages 357-369

  Xie, Xianghua ^a  

^a SWANSEA UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOUR MODEL; ACTIVE CONTOURS; BACKGROUND REGION; BIN SIZE; DIRECT MODELING; IMAGE FEATURES; LEVEL SET; LOCAL HISTOGRAM; NON-UNIFORMITIES; REAL-WORLD IMAGE; ROTATION INVARIANT; SNAKE SEGMENTATION; SPECTRAL HISTOGRAM; SYNTHETIC AND REAL DATA; TEXTURED IMAGES; UNDERLYING DISTRIBUTION;

COMPUTER GRAPHICS; COMPUTER VISION; GRAPHIC METHODS; STATISTICAL METHODS;

IMAGE SEGMENTATION;

EID: 77957583782     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-11840-1_26     Document Type: Conference Paper

References (30)

1. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contour. International Journal of Computer Vision 22, 61-79 (1997)
2. Malladi, R., Sethian, J.A., Vemuri, B.C.: Shape modelling with front propagation: A level set approach. IEEE Transations on Pattern Analysis and Machine Intelligence 17, 158-175 (1995)
3. Xu, C., Prince, J.: Snakes, shapes, & gradient vector flow. IEEE Transactions on Image Processing 7, 359-369 (1998)
4. Xie, X., Mirmehdi, M.: RAGS: Region-aided geometric snake. IEEE Transactions on Image Processing 13, 640-652 (2004)
5. Kass, M., Witkin, A., Terzopoulus, D.: Snakes: Active contour model. International Journal of Computer Vision 1, 321-331 (1988)
6. McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: A survey. Medical Image Analysis 1, 91-108 (1996)
7. Sandberg, B., Chan, T., Vese, L.: In: A level-set and gabor-based active contour algorithm for segmenting textured images. Technical Report 39, Math. Department UCLA, Los Angeles, USA (2002)
8. Ni, K., Bresson, X., Chan, T., Esedoglu, S.: Local histogram based segmentation using the Wasserstein distance. In: Scale Space and Variational Methods in Computer Vision, pp. 697-708 (2007)
9. Houhou, N., Thiran, J.: Fast texture segmentation model based on the shape operator and active contour. In: IEEE Conference on Computer Vision Pattern Recognition, pp. 1-8 (2008)
10. Savelonas, M., Iakovidis, D., Maroulis, D.: LBP-guided active contours. Pattern Recognition Letters 29, 1404-1415 (2008)
11. Paragios, N., Mellina-Gottardo, O., Ramesh, V.: Gradient vector flow geometric active contours. IEEE Transations on Pattern Analysis and Machine Intelligence 26, 402-407 (2004)
12. Xie, X., Mirmehdi, M.: MAC: Magnetostatic active contour model. IEEE Transations on Pattern Analysis and Machine Intelligence 30, 632-646 (2008)
13. Pujol, O., Radeva, P.: Texture segmentation by statistical deformable models. International Journal of Image and Graphics 4, 433-452 (2004)
14. Rousson, M., Brox, T., Deriche, R.: Active unsupervised texture segmentation on a diffusion based feature space. In: IEEE Conference on Computer Vision Pattern Recognition, pp. 1-8 (2004)
15. Paragios, N., Deriche, R.: Geodesic active regions and level set methods for supervised texture segmentation. International Journal of Computer Vision 46, 223-247 (2002)
16. Aujol, J., Aubert, G., Blanc-Féraud, L.: Wavelet-based level set evolution for classification of textured images. IEEE Transactions on Image Processing 12, 1634-1641 (2003)
17. He, Y., Luo, Y., Hu, D.: Unsupervised texture segmentation via applying geodesic active regions to Gaborian feature space. World Academy of Science, Engineering and Technology 2, 200-203 (2005)
18. Sagiv, C., Sochen, N., Zeevi, I.: Integrated active contours for texture segmentation. IEEE Transactions on Image Processing 15, 1633-1645 (2006)
19. Chan, T., Vese, L.: Active contours without edges. IEEE Transactions on Image Processing 10, 266-277 (2001)
20. Azencott, R., Wang, J., Younes, L.: Texture classification using windowed fourier filters. IEEE Transations on Pattern Analysis and Machine Intelligence 19, 148-153 (1997)
21. Dunn, D., Higgins, W., Wakeley, J.: Texture segmentation using 2-d gabor elementary functions. IEEE Transations on Pattern Analysis and Machine Intelligence 16, 130-149 (1994)
22. Heeger, D., Bergen, J.: Pyramid-based texture analysis/synthesis. In: Computer graphics and interactive techniques, pp. 229-238 (1995)
23. Xie, X., Mirmehdi, M.: TEXEMS: Texture exemplars for defect detection on random textured surfaces. IEEE Transations on Pattern Analysis and Machine Intelligence 29, 1454-1464 (2007)
24. Varma, M., Zisserman, A.: Classifying images of materials: Achieving viewpoint and illumination independence. In: IEEE European Conference on Computer Vision, pp. 255-271 (2002)
25. Jacob, M., Unser, M.: Design of steerable filters for feature detection using Canny-like criteria. IEEE Transations on Pattern Analysis and Machine Intelligence 26, 1007-1019 (2004)
26. Geusebroek, J., Smeulders, A., van de Weijer, J.: Fast anisotropic gauss filtering. IEEE Transactions on Image Processing 12, 938-943 (2003)
27. Liu, X., Wang, D.: Texture classification using spectral histograms. IEEE Transactions on Image Processing 12(6), 661-670 (2003)
28. Liu, X., Wang, D.: Image and texture segmentation using local spectral histograms. IEEE Transactions on Image Processing 15, 3066-3077 (2006)
29. Shimazaki, H., Shinomoto, S.: A method for selecting the bin size of a time histogram. Neural Computation 19, 1503-1527 (2007)
30. Rubner, Y., Tomasi, C., Guibas, L.: A metric for distributions with applications to image databases. In: IEEE Conference on Computer Vision Pattern Recognition, pp. 59-66 (1998)