Image thresholding by variational minimax optimization

Pattern Recognition

Volumn 42, Issue 5, 2009, Pages 843-856

  Saha, Baidya Nath ^a   Ray, Nilanjan ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Image thresholding; Minimax optimization; Variational calculus

Indexed keywords

ADAPTIVE ALGORITHMS; FUNCTIONS; KNOWLEDGE BASED SYSTEMS; OPTIMIZATION; VARIATIONAL TECHNIQUES;

ADAPTIVE IMAGES; CONVEX COMBINATIONS; DATA FIDELITIES; ENERGY FUNCTIONAL; IMAGE SURFACES; IMAGE THRESHOLDING; ITERATIVE GRADIENTS; LARGE IMAGES; LINE SEARCHES; MINIMAX; MINIMAX OPTIMIZATION; MINIMAX PRINCIPLES; OPTIMUM SOLUTIONS; PARAMETER VALUES; REGULARIZATION TERMS; SENSITIVE DATUMS; THRESHOLD SURFACES; VARIATIONAL CALCULUS; VARIATIONAL FORMULATIONS;

EDGE DETECTION;

EID: 58249085167     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.09.033     Document Type: Article

References (24)

1. Gonzalez R.C., and Woods R.E. Digital Image Processing (2005), Pearson Prentice-Hall
2. Otsu N. A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. SMC-9 1 (1979) 62-66
3. Sahoo P.K., Soltani S., Wong A.K.C., and Chen Y. A survey of thresholding techniques. Comput. Vision Graphics Image Process. 41 (1988) 233-260
4. Kittler J., and Illingworth J. Minimum error thresholding. Pattern Recognition 19 1 (1986) 41-47
5. Niblack W. An Introduction to Digital Image Processing (1986), Prentice-Hall, Englewood Cliffs, NJ
6. Jain R., Kasturi R., and Schunk B.G. Machine Vision (1995), McGraw-Hill, New York
7. Chow C.K., and Kaneko T. Automatic boundary detection of the left-ventricle from cineangiograms. Comput. Biomed. Res. 5 (1972) 388-410
8. D.L. Milgram, A. Rosenfeld, T. Willet, G. Tisdale, Algorithms and hardware technology for image recognition, Final Report to US Army Night Vision Lab., Computer Science Centre, University Maryland, College park, 1978.
9. Yanowitz S.D., and Bruckstein A.M. A new method for image segmentation. Comput. Vision Graphs Image process. 46 (1989) 82-95
10. Yan F., Zhang H., and Kube C.R. Multistage adaptive thresholding method. Pattern Recognition Lett. 26 8 (2005) 1183-1191
11. Chan F.H.Y., Lam F.K., and Zhu H. Adaptive thresholding by variational method. IEEE Trans. Image Process. 7 3 (1998) 468-473
12. Liu F., Luo Y., Song X., and Hu D. Active surface model-based adaptive thresholding algorithm by repulsive external force. J. Electron. Imaging 12 (2003) 299-306
13. Shen D., and Ip H.H.S. A Hopfield neural network for adaptive image segmentation: An active surface paradigm. Pattern Recognition Lett. 18 (1997) 37-48
14. Li X., Ramachandran R., He M., Movva S., Rushing J., Graves S., Lyatsky W., Tan A., and Germany G. Comparing different thresholding algorithms for segmenting auroras. Proc. Int. Conf. Inf. Technol.: Coding Comput. 2 (2004) 594-601
15. Sezgin M., and Sankur B. Survey over image thresholding techniques and quantitative performance evaluation. J. Electron. Imaging 13 (2004) 146-165
16. N. Ray, B. Saha, Edge Sensitive Variational Image Thresholding, accepted at IEEE International Conference on Image Processing, September 2007.
17. M.A. Gennert, A.Y. Yuille, Determining the optimal weights in multiple objective function optimization, in: Proceedings of the Second International Conference on Computer Vision, 1988, pp. 87-89.
18. Ruszczynski A. Nonlinear Optimization (2006), Princeton University Press, Princeton, NJ
19. Evans G., Blackledge J., and Yardley P. Numerical Methods for Partial Differential Equations (2005), Springer, Berlin
20. Ray N., Acton S.T., Altes T., de Lange E.E., and Brookeman J.R. Merging parametric active contours within Homogeneous Image Regions for MRI-Based Lung Segmentation. IEEE Trans. Med. Imaging 22 (2003) 189-199
21. Bezdek J.C., Keller J., Krishnapuram R., and Pal N.R. Fuzzy Models and Algorithms for Pattern Recognition and Image Processing (1999), Springer, Berlin
22. Abdou I.E., and Pratt W.K. Quantitative design and evaluation of enhancement/thresholding edge detectors. Proc. IEEE 67 5 (1979) 753-763
23. Troutman J.L. Variational Calculus with Elementary Convexity (1983), Springer, Berlin
24. Fletcher R. Practical Methods of Optimization. second ed. (2006), Wiley, New York