@article{(Open Science Index):https://publications.waset.org/pdf/12045,
	  title     = {Contour Estimation in Synthetic and Real Weld Defect Images based on Maximum Likelihood},
	  author    = {M. Tridi and  N. Nacereddine and  N. Oucief},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper describes a novel method for automatic
estimation of the contours of weld defect in radiography images.
Generally, the contour detection is the first operation which we apply
in the visual recognition system. Our approach can be described as a
region based maximum likelihood formulation of parametric
deformable contours. This formulation provides robustness against
the poor image quality, and allows simultaneous estimation of the
contour parameters together with other parameters of the model.
Implementation is performed by a deterministic iterative algorithm
with minimal user intervention. Results testify for the very good
performance of the approach especially in synthetic weld defect
images.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {9},
	  year      = {2007},
	  pages     = {2894 - 2897},
	  ee        = {https://publications.waset.org/pdf/12045},
	  url   	= {https://publications.waset.org/vol/9},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 9, 2007},
	}