DocumentCode :
2989597
Title :
Fairing Material Grain Contour Detection
Author :
Zhao Xiuyang ; Wang YaNan ; Yang Bo ; Zhang Caiming
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
fYear :
2009
fDate :
18-20 Jan. 2009
Firstpage :
1
Lastpage :
4
Abstract :
On the basis of the modified Chan-Vese model and genetic algorithm, a new contour acquired method for image segmentation is presented. In the method, the raw contours were acquired by using the modified Chan-Vese model. The model is able to detect all the objects or details in the image. After that, the genetic algorithm was used to optimize the raw contours. The data points are respected as variables. The contours were then modeled as a continuous, nonlinear and multivariate optimization problem with many local optima. For this reason it is very difficult to reach a global optimum. In this paper, we convert the original problem into a discrete combinatorial optimization problem. The proposed method determines the appropriate contour location of the SiC/Al composite image automatically and simultaneously. The results show that our method is efficiency and effective.
Keywords :
genetic algorithms; image segmentation; Chan-Vese model; continuous optimization; contour acquired method; discrete combinatorial optimization problem; fairing material grain contour detection; genetic algorithm; image segmentation; modified Chan-Vese model; multivariate optimization problem; nonlinear optimization; Active contours; Composite materials; Computer science; Genetic algorithms; Genetic engineering; Image segmentation; Information science; Materials science and technology; Microstructure; Object detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5272-9
Type :
conf
DOI :
10.1109/CNMT.2009.5374708
Filename :
5374708
Link To Document :
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