文件名称:IJETTCS-2012-08-24-100
- 所属分类：
- 软件工程
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- [PDF]
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- 2015-10-18
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- 206kb
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- 提 供 者：
- Merin Il*********
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Image segmentation by region growing method is
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms.-Image segmentation by region growing method is
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms.
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms.-Image segmentation by region growing method is
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms.
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IJETTCS-2012-08-24-100.pdf