[1]
J. -P. Wang, Stochastic relaxation on partitions with connected components and its application to image segmentation, IEEE Trans. Pattern Analysis and Machine Intelligence, 20. 6 (1998) 619-636.
DOI: 10.1109/34.683775
Google Scholar
[2]
H. Min, W. Jia, X. -F. Wang, Y. Zhao, R. -X. Hu, Y. -T. Luo, F. Xue, J. -T. Lu, An intensity-texture model based level set method for image segmentation, Pattern Recognition, 48. 4 (2015) 1547-1562.
DOI: 10.1016/j.patcog.2014.10.018
Google Scholar
[3]
B. Peng, L. Zhang, D. Zhang, Automatic image segmentation by dynamic region merging, IEEE Trans. Image Process, 12 (2011) 3592-3605.
DOI: 10.1109/tip.2011.2157512
Google Scholar
[4]
P. Felzenszwalb D. Huttenlocher, Efficient graph-based image segmentation, Int. J. Comput. Vis., 59 (2004) 167-181.
Google Scholar
[5]
J. Shi and J. Malik, Normalized cuts image segmentation, IEEE Trans. Pattern Analysis and Machine Intelligence, 22. 8 (2000) 888-905.
DOI: 10.1109/34.868688
Google Scholar
[6]
L. Shafarenko, M. Petrou, J. Kittler, Automatic watershed segmentation of randomly textured color Images, IEEE Trans. Image Processing, 6. 11 (1997) 1530-1544.
DOI: 10.1109/83.641413
Google Scholar
[7]
R. Gaetano, G. Masi, G. Poggi, L. Verdoliva G. Scarpa, Marker-controlled watershed-based segmentation of multiresolution remote sensing images, IEEE Transactions on Geoscience and Remote Sensing, 53. 6 (2014) 2987-3004.
DOI: 10.1109/tgrs.2014.2367129
Google Scholar
[8]
K. Zhang, H. Song, L. Zhang, Active contours driven by local image fitting energy, Pattern Recognition, 43. 4 (2010) 1199-1206.
DOI: 10.1016/j.patcog.2009.10.010
Google Scholar
[9]
B. Wang, X. Gao, D. Tao X. Li, Unified tensor level set for image segmentation, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 40. 3 (2010) 857-867.
DOI: 10.1109/tsmcb.2009.2031090
Google Scholar
[10]
Y. Deng, B.S. Manjunath, Unsupervised segmentation of color-texture regions in images and video, IEEE Trans. Pattern Analysis and Machine Intelligence, 23. 8 (2001) 800-810.
DOI: 10.1109/34.946985
Google Scholar
[11]
Y. Deng, C. Kenney, M.S. Moore, B.S. Manjunath, Peer group filtering and perceptual color image quantization, in Proc. IEEE Int'l Symp. Circuits and Systems, 4 (1999) 21-24.
DOI: 10.1109/iscas.1999.779933
Google Scholar
[12]
J. Schanda, Colorimetry: Understanding the CIE system, Wiley Interscience. p.61–64, (2007).
Google Scholar
[13]
S. W. Yoon, H. S. Shin, S. D. Min and M. Lee, Medical endoscopic image segmentation with multi-resolution deformation, in Proc. 2007 9th International Conference on e-Health Networking, Application and Services, (2007) 256-259.
DOI: 10.1109/health.2007.381643
Google Scholar
[14]
M. P. Tjoa, S. M. Krishnan, C. Kugean, P. Wang and R. Doraiswami, Segmentation of clinical endoscopic image based on homogeneity and hue, in Proc. 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 3 (2001).
DOI: 10.1109/iembs.2001.1017331
Google Scholar
[15]
S. M. Alsaleh, A. I. Aviles, P. Sobrevilla, A. Casals and J. K. Hahn, Adaptive segmentation and mask-specific Sobolev inpainting of specular highlights for endoscopic images, in Proc. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (2016).
DOI: 10.1109/embc.2016.7590919
Google Scholar
[16]
T. Okamoto et al., Image segmentation of pyramid style identifier based on support vector machine for colorectal endoscopic images, in Proc. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (2015).
DOI: 10.1109/embc.2015.7319022
Google Scholar
[17]
T. Hirakawa et al., SVM-MRF segmentation of colorectal NBI endoscopic images, in Proc. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, (2014) 4739-4742.
DOI: 10.1109/embc.2014.6944683
Google Scholar
[18]
R. S. Hegadi, Segmentation of tumors from endoscopic images using topological derivatives based on discrete approach, in Proc. 2010 International Conference on Signal and Image Processing, (2010) 54-58.
DOI: 10.1109/icsip.2010.5697441
Google Scholar
[19]
I. N. Figueiredo, P. N. Figueiredo, G. Stadler, O. Ghattas and A. Araujo, Variational image segmentation for endoscopic human colonic aberrant crypt foci, IEEE Transactions on Medical Imaging, 29. 4 (2010) 998-1011.
DOI: 10.1109/tmi.2009.2036258
Google Scholar
[20]
B. V. Dhandra, R. Hegadi, M. Hangarge and V. S. Malemath, Analysis of abnormality in endoscopic images using combined HSI color space and watershed segmentation, in Proc. 18th International Conference on Pattern Recognition, (2006) 695-698.
DOI: 10.1109/icpr.2006.268
Google Scholar
[21]
C. Barbalata and L. S. Mattos, Laryngeal tumor detection and classification in endoscopic video, IEEE Journal of Biomedical and Health Informatics, 20. 1 (2016) 322-332.
DOI: 10.1109/jbhi.2014.2374975
Google Scholar