A mixed model of active geodesic contours with gradient vector flows for X-ray microtomography segmentation

The structural characterization of weathered building stones of historical monuments can be achieved with a powerfull imagering technique, X-ray microtomography. It requires however a carefull extraction of each phase constituting the sample from the raw gray-level images obtained (the segmentation process). This contribution presents an original method of segmentation of such images that combines active contour models driven by gradient vector flows with a morphological preprocessing, alternate sequential filters. Preliminary results on high resolution, structuraly complex images are presented and compared to more classical approaches.

[1]  P. Cloetens,et al.  X-ray micro-tomography an attractive characterisation technique in materials science , 2003 .

[2]  P. Cloetens,et al.  Advances in synchrotron radiation microtomography , 2006 .

[3]  Jerry L. Prince,et al.  Gradient vector flow: a new external force for snakes , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  S. Osher,et al.  Level set methods: an overview and some recent results , 2001 .

[5]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[6]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[7]  G. Matheron Random Sets and Integral Geometry , 1976 .

[8]  Emilio Galán,et al.  A methodology for locating the original quarries used for constructing historical buildings: application to Málaga Cathedral, Spain , 1999 .

[9]  Emmanuel Le Trong,et al.  2-D image analysis: A complementary tool for characterizing quarry and weathered building limestone , 2007 .

[10]  R. Deriche,et al.  Les EDP en traitement des images et vision par ordinateur , 1995 .

[11]  A. Yezzi,et al.  On the relationship between parametric and geometric active contours , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[12]  X. Thibault,et al.  Synchrotron radiation microtomography applied to investigation of paper , 2005 .

[13]  Anthony J. Yezzi,et al.  Gradient flows and geometric active contour models , 1995, Proceedings of IEEE International Conference on Computer Vision.

[14]  Laurence Guillot,et al.  Existence and uniqueness results for the gradient vector flow and geodesic active contours mixed model , 2007 .

[15]  Adrian Sheppard,et al.  Techniques for image enhancement and segmentation of tomographic images of porous materials , 2004 .

[16]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[17]  Avinash C. Kak,et al.  Principles of computerized tomographic imaging , 2001, Classics in applied mathematics.

[18]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.