Abstract
This chapter deals with the problem of image modelling through the use of 2D Markov Random Field (MRF). The MRF’s are parametric models with a noncausal structure where the various dependencies over the plane is described in all directions. We first show how the MRF’s are used as texture image models, region geometry models, as well as edge models.Then we show how they have been successfully used for image classification, surface inspection, image restoration, and image segmentation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Reference
M. S. Bartlett, London: Chapman and Hall, 1976.
J. Besag, J. Royal Statis. Soc., Series B, Vol. 36, pp 192–326,1974.
R. Chellappa and R. L. Kayshap, IEEE Trans. ASSP, Vol. ASSP-30, pp. 461–472,1982.
F. S. Cohen and D. B. Cooper, Proc. of the 3rd Int. Conf. on Robot Vision & Sensory Control, Cambridge, MA, SPIE 449, pp. 17–28, Nov. 1983.
F. S. Cohen, D. B. Cooper, J. F. Silverman, & E. B. Hinkle, Proc. of the 7th Int. Conf. on Pattern Recognition, Montreal, Canada, pp. 1104–1107, 1984.
F. S. Cohen and D. B. Cooper, Accepted for Publication in IEEE Trans. PAMI. Also appears as Tech. Rep., Division of Eng., Brown Univ., Prov., RI 02912, July 1984.
Z. Fan and F. S. Cohen, Tech-Rep., Electr. Eng. Dept., Univ. of Rhode Island, Kingston, RI 02881, Jan. 1986.
F. S. Cohen and Z. Fan, Tech-Rep., Electr. Eng. Dept., Univ. of Rhode Island, Kingston, RI 02881, March 1986.
F. S. Cohen, S. F. Aitali, and Z. Fan, Tech-Rep., Electr. Eng. Dept., Univ. of Rhode Island, Kingston, RI 02881, May 1986.
G. C. Cross, Tech. Rep. 80–02, Dept. of Comp. Sc., College of Eng., Michigan State Univ., 1980.
G. C. Cross and A. K. Jain, IEEE Trans. Pami, Vol. PAMI-5, pp. 25–39,1983.
H. Elliot, H. Derin, R. Cristi and D. Geman, Proc. IEEE 1985 ICASSP, March 1985.
H. Elliot and H. Derin, Tech. Rep., Elect. Comp. Eng. Dept., Univ. of Mass., Amherst, MA 01003, Sept. 1984.
S. Geman and D. Geman, IEEE Trans. PAMI, Vol. 6, No. 6, pp. 721–741, Nov. 1984.
R. L. Kashyap and R. Chellappa, IEEE Trans. Inf. Theory, Vol. IT-29, pp 60–72,1983.
R. Kinderman and J. L. Snell, Amer. Math. Soc., 1980, Providence, RI.
J. Woods, IEEE Trans. Inf. Theory, Vol. 18, pp. 232–240, March 1972.
S. Zacks, Pergamon 1981.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1986 Kluwer Academic Publishers, Boston
About this chapter
Cite this chapter
Cohen, F.S. (1986). Markov Random Fields for Image Modelling & Analysis. In: Desai, U.B. (eds) Modelling and Application of Stochastic Processes. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-2267-2_10
Download citation
DOI: https://doi.org/10.1007/978-1-4613-2267-2_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-9400-9
Online ISBN: 978-1-4613-2267-2
eBook Packages: Springer Book Archive