Open Access
ABSTRACT
Modeling Intergranular Stress Corrosion Cracking A Voronoi-Markovian-Monte Carlo Approach
The International Conference on Computational & Experimental Engineering and Sciences 2009, 13(3), 59-60. https://doi.org/10.3970/icces.2009.013.059
Abstract
This paper introduce a novel approach for face image segmentation base on Voronoi Diagram (VD) technique. We used intensity value and region pixels value for enhance preprocessing step on gray-scale image. The method for locating and extraction face/head boundary are applied feature point of the original image which are useful dual tessellation of the VD is know as Delaunay Triangulation (DT). A target of experiment is reported face image segmentation that uses still face image from BioID database. The result of this method clearly demonstrates the segmentation which performs in comparison with another method in quality of gray value and speed. It indicates a new alternative approach that can be used for face segmentation, detection, and extraction which are the next steps of the entire face recognition system.Cite This Article
APA Style
Arafin, M., Szpunar, J. (2009). Modeling intergranular stress corrosion cracking A voronoi-markovian-monte carlo approach. The International Conference on Computational & Experimental Engineering and Sciences, 13(3), 59-60. https://doi.org/10.3970/icces.2009.013.059
Vancouver Style
Arafin M, Szpunar J. Modeling intergranular stress corrosion cracking A voronoi-markovian-monte carlo approach. Int Conf Comput Exp Eng Sciences . 2009;13(3):59-60 https://doi.org/10.3970/icces.2009.013.059
IEEE Style
M. Arafin and J. Szpunar, “Modeling Intergranular Stress Corrosion Cracking A Voronoi-Markovian-Monte Carlo Approach,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 13, no. 3, pp. 59-60, 2009. https://doi.org/10.3970/icces.2009.013.059
Copyright © 2009 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.