Automatic colour–texture image segmentation using active contours

References

• Sifakis , E. , Garcia , C. and Tziritas , G. 2002 . Bayesian level sets for image segmentation . Journal of Visual Communication and Image Representation , 13 : 44 – 64 .
   Web of Science ®Google Scholar
• Zhu , S. and Yuille , A. 1996 . Region competition: unifying snakes, region growing and Bayes/MDL for multiband image segmentation . IEEE Transactions on Pattern Analysis and Machine Intelligence , 18 : 884 – 900 .
   Web of Science ®Google Scholar
• Jain , A. and Farrokhnia , F. 1991 . Unsupervised texture segmentation by using Gabor filters . Pattern Recognition , 24 : 1167 – 1186 .
   Web of Science ®Google Scholar
• Liapis , S. , Sifakis , E. and Tziritas , G. 2004 . Colour and texture segmentation using wavelet frame analysis, deterministic relaxation and fast marching algorithms . Journal of Visual Communication and Image Representation , 15 : 1 – 26 .
   Google Scholar
• Paragios , N. and Deriche , R. 2002 . Geodesic active regions and level set methods for supervised texture segmentation . International Journal of Computer Vision , 46 : 223 – 247 .
   Web of Science ®Google Scholar
• Carson , C. , Belongie , S. , Greenspan , H. and Malik , J. 2002 . Blobworld: image segmentation using expectation-maximization and its application to image querying . IEEE Transactions on Pattern Analysis and Machine Intelligence , 24 : 1026 – 1038 .
   Web of Science ®Google Scholar
• Haindl , M. and Mikes , S. Colour texture segmentation using modelling approach . Third International Conference on Advances in Pattern Recognition, ICAPR . August 22–25 2005 , Bath, UK. Pattern Recognition and Image Analysis , Edited by: Singh , S. , Singh , M. , Apté , C. and Perner , P. Vol. 3687 , pp. 484 – 491 . Proceedings, Part II. Lecture Notes in Computer Science
   Google Scholar
• Goldberger , J. and Greenspan , H. 2006 . Context-based segmentation of image sequences . IEEE Transactions on Pattern Analysis and Machine Intelligence , 28 : 463 – 468 .
   PubMed Web of Science ®Google Scholar
• Tao , D. , Li , X. , Wu , X. and Maybank , S. Human carrying status in visual surveillance . Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition . Vol. 2 , pp. 1670 – 1677 .
   Google Scholar
• Lutton , E. 3D model based stereo reconstruction using coupled Markov random fields . Proceedings of the 5th International Conference on Computer Analysis of Images and Patterns . Lecture Notes in Computer Scienc , Vol. 719 , pp. 494 – 501 .
   Google Scholar
• Tao , D. , Li , X. , Hu , W. , Maybank , S. and Wu , X. Supervised tensor learning . Proceedings of the Fifth IEEE International Conference on Data Mining . pp. 450 – 457 .
   Google Scholar
• Osher , S. and Sethian , J. 1988 . Fronts propagating with curvature-dependant speed: algorithms based on Hammilton–Jacobi formulations . Journal of Computational Physics , 79 : 12 – 49 .
   Web of Science ®Google Scholar
• Rousson , M. , Brox , T. and Deriche , R. Active unsupervised texture segmentation on a diffusion based feature space . Proceedings of the 2003 IEEE International Conference on Computer Vision and Pattern Recognition . Vol. 2 , pp. 699 – 704 .
   Google Scholar
• Unal , G. B. , Yezzi , A. J. and Krim , H. 2004 . Information-theoretic active polygons for unsupervised texture segmentation . International Journal of Computer Vision , 62 : 199 – 220 .
   Google Scholar
• Chan , T. F. and Vese , L. 2001 . Active contours without edges . IEEE Transactions on Image Processing , 10 : 266 – 277 .
   PubMed Web of Science ®Google Scholar
• Allili , M. S. and Ziou , D. An automatic segmentation combining mixture analysis and adaptive region information: a level set approach . Proceedings of the 2nd Canadian Conference on Computer and Robot Vision . pp. 73 – 80 .
   Google Scholar
• Yezzi , A. , Tsai , A. and Willsky , A. 2002 . A fully global approach to image segmentation via couples curve evolution equations . Journal of Visual Communication and Image Representation , 13 : 195 – 216 .
   Google Scholar
• Drewniok , C. 1994 . Multispectral edge detection: some experiments on data from Landsat-TM . International Journal of Remote Sensing , 15 : 3743 – 3765 .
   Web of Science ®Google Scholar
• Huang , J. , Kumar , S. R. , Mitra , M. , Zhu , W.-J. and Zabih , R. Image indexing using colour correlograms . Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition . pp. 762 – 768 .
   Google Scholar
• Akaike , H. 1974 . A new look at the statistical model identification . IEEE Transactions on Automatic Control , 19 : 716 – 723 .
   Web of Science ®Google Scholar
• Haralick , R. M. and Shapiro , L. G. 1985 . Survey: image segmentation techniques . Computer Vision Graphics and Image Processing , 29 : 100 – 132 .
   Google Scholar
• Li , X. , Yuan , T. , Yu , N. and Yuan , Y. 2003 . Adaptive colour quantization based on perceptive edge protection . Pattern Recognition Letters , 24 : 3165 – 3176 .
   Web of Science ®Google Scholar
• Caselles , V. , Kimmel , R. and Sapiro , G. 1997 . Geodesic active contours . International Journal of Computer Vision , 22 : 61 – 79 .
   Web of Science ®Google Scholar
• Mikes , S. and Haindl , M. 2006 . Prague texture segmentation data generator and benchmark . ERCIM News , 64 : 67 – 68 .
   Google Scholar
• Hoover , A. , Jean-Baptiste , G. , Jiang , X. , Flynn , P. J. , Bunke , H. , Goldgof , D. B. , Bowyer , K. , Eggert , D. W. , Fitzgibbon , A. and Fisher , R. B. 1996 . An experimental comparison of range image segmentation algorithms . IEEE Transactions on Pattern Analysis and Machine Intelligence , 18 : 673 – 689 .
   Web of Science ®Google Scholar
• Martin , D. , Fowlkes , C. , Tal , D. and Malik , J. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics . Proceedings of the Eighth IEEE International Conference on Computer Vision . Vol. 2 , pp. 416 – 423 .
   Google Scholar