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一种改进的势函数聚类多阈值图像分割算法
Improved multi-threshold image segmentation algorithm based on potential function clustering
查看参考文献9篇
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文摘
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针对基于势函数聚类的多阈值图像分割算法的不足，定义了伪势的概念，并在原算法基础上提出了一种改进的图像分割算法。由伪势概念确定了伪势合并的判别方法，按照此方法，当相邻的两个峰之间的距离小于所定义的自适应模糊伪势因子时，则应该进行伪势合并。改进后的算法在计算剩余势函数时判断是否存在伪势，然后在势划分函数组的确定过程中相应地进行伪势合并计算。利用多幅图像进行了多阈值分割的仿真试验，结果表明，改进的基于势函数的多阈值图像分割算法具有更好的鲁棒性和分割效果。[著者文摘] |
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其他语种文摘
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Aiming at the disadvantage of multi-threshold image segmentation algorithm based on potential function clustering, a concept of false potential is defined and an improved image segmentation algorithm is proposed on the basis of an original algorithm. According to this method, when the distance between the adjacent peaks is less than the adaptive fuzzy false potential factor, the false potential mergence should be implemented. The improved algorithm will judge if there are false potentials when calculating the residual potential function and if false potentials exist, implement false potential mergence in the process of dividing the potential function groups. The segmentation experiment for several images shows that the improved algorithm possesses better segmentation and more robust performance than the original algorithm. |
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来源
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光电工程
,2005,32(8):64-68 【核心库】
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关键词
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图像分割
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势函数
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多阂值
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鲁棒性
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地址
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中国科学院沈阳自动化研究所, 辽宁, 沈阳, 110016
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1003-501X |
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学科
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自动化技术、计算机技术 |
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基金
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中国科学院科技创新基金
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文献收藏号
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CSCD:2097632
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参考文献 共
9
共1页
|
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1.
OLGA R P. New improvements to range image segmentation by edge detection [J].
IEEE Signal Processing Letters,2002,9(2):43-45
|
被引
1
次
|
|
|
|
|
2.
章毓晋. 图像分割[M].
图像分割,2001
|
被引
449
次
|
|
|
|
|
3.
ZHANG Y J. A review of recent evaluation methods for image segmentation[A].
Proceedings of the International Symposium on Signal Processing and its Applications,2001:148-151
|
被引
1
次
|
|
|
|
|
4.
罗希平. 图像分割方法综述.
模式识别与人工智能,1999,12(3):300-312
|
被引
68
次
|
|
|
|
|
5.
FERNANDES D N. Architecture of oscillatory neural network for image segmentation[A].
Proceedings of the 14th Symposium on Computer Architecture and High Performance Computing,2002:29-36
|
被引
1
次
|
|
|
|
|
6.
MARKOU M. Neural network analysis of MINERVA scene analysis benchmark[A].
Proceedings of 11th International Conference on Image Analysis and Processing,2001:267-272
|
被引
1
次
|
|
|
|
|
7.
陈佳娟. 一种基于纹理信息和遗传神经网络的图像分割方法.
计算机工程,2002,28(9):86-88
|
被引
1
次
|
|
|
|
|
8.
裴继红. 势函数聚类自适应多阈值图像分割.
计算机学报,1999,22(7):758-762
|
被引
18
次
|
|
|
|
|
9.
施法中. 计算机辅助几何设计与非均匀有理B样条[M].
计算机辅助几何设计与非均匀有理B样条,1994
|
被引
402
次
|
|
|
|
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