Color image segmentation guided by a color gradient network

Pattern Recognition Letters

Volumn 28, Issue 13, 2007, Pages 1795-1803

  Wangenheim, Aldo v ^a   Bertoldi, Rafael F ^a   Abdala, Daniel D ^b   Richter, Michael M ^c  

^a FEDERAL UNIVERSITY OF SANTA CATARINA   (Brazil)

^b UNIVERSITY OF MÜNSTER   (Germany)

^c UNIVERSITY OF CALGARY   (Canada)

Author keywords

Color gradient networks; Natural color scenes; Region growing segmentation

Indexed keywords

COLOR GRADIENT NETWORK; COLOR IMAGE SEGMENTATION; SEGMENTATION ALGORITHMS;

COLOR IMAGE PROCESSING; ERROR DETECTION; IMAGE ENHANCEMENT; PIXELS; PROBLEM SOLVING;

IMAGE SEGMENTATION;

EID: 34447324609     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2007.05.009     Document Type: Article

References (16)

1. Deng Y., and Manjunath B.S. Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. Pattern Anal. Machine Intell. 23 8 (2001) 800-810
2. Dony, R.D., Wesolkowski, S.B. 1999. Edge detection on color images using RGB vector angles. In: Proc. 1999 IEEE Canadian Conf. Electrical and Computer Engineering. Edmonton, Alberta, Canada May 9-12, pp. 687-692.
3. Dupuis A., and Vasseur P. Image segmentation by cue selection and integration. Image Vision Comput. 24 10 (2006) 1053-1064 October
4. Huang K., Wang Q., and Wu Z. Natural color image enhancement and evaluation algorithm based on human visual system. Computer Vision Image Understand. 103 1 (2006) 52-63 July
5. Kato Z., and Pong T.C. A Markov random field image segmentation model for color textured images. Image Vision Comput. 24 10 (2006) 1103-1114 October
6. Martin, D., Fowlkes, C., Tal, D., Malik, J. 2001. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proc. 8th Internat. Conf. on Computer Vision, vol. 2. pp. 416-423.
7. Megawave Homepage: , 2006 (accessed 14.9.06).
8. Mittelheusser G., and Kruggel F. Fast Segmentation of Brain Magnetic Resonance Tomograms. CVRMed'95: First International Conference on Computer Vision, Virtual reality and Robotics in Medicine, INRIA, Nizza (1995), Springer Verlag April
9. Mumford D., and Shah J. Optimal approximations by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42 (1989) 577-684
10. Priese L., and Rehrmann V. A fast hybrid color segmentation method. DAGM-Symposium (1993) 297-304
11. Rehrmann V., and Priese L. Fast and robust segmentation of natural color scenes. ACCV 1 (1998) 598-606
12. Schneider M.K., Fieguth P.W., Karl W.C., and Willsky A.S. Multiscale methods for the segmentation and reconstruction of signals and images. IEEE Trans. Image Process. 9 3 (2000) 456-468 March
13. Tilton, J.C., D-dimensional formulation and implementation of recursive hierarchical segmentation, Disclosure of Invention and New Technology: NASA Case No. GSC 15199-1, May 26, 2006.
14. Trémeau A., and Colantoni P. Regions adjacency graph applied to color image segmentation. IEEE Trans. Image Process. 9 4 (2000) 735-744
15. Vincent L., and Soille P. Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Machine Intell. 13 (1991) 583-598
16. Wu Z., and Leahy R. An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation. IEEE Trans. Pattern Anal. Machine Intell. 15 11 (1993) 1101-1113 Nov