[1]李万臣,葛秘蕾,井志强.基于云理论的图像分割新方法[J].应用科技,2010,37(03):45-48.[doi:10.3969/j.issn.1009-671X.2010.03.012]
 LI Wan-chen,GE Mi-lei,JING Zhi-qiang.A new method of image segmentation based on cloud theory[J].Applied science and technology,2010,37(03):45-48.[doi:10.3969/j.issn.1009-671X.2010.03.012]
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《应用科技》[ISSN:1009-671X/CN:23-1191/U]

卷:
第37卷
期数:
2010年03期
页码:
45-48
栏目:
现代电子技术
出版日期:
2010-03-05

文章信息/Info

Title:
A new method of image segmentation based on cloud theory
文章编号:
1009- 671X(2010)03- 0045- 04
作者:
李万臣葛秘蕾井志强
哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001
Author(s):
LI Wan-chenGE Mi-lei JING Zhi-qiang
(College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China)
关键词:
云理论云变换区域生长图像分割
Keywords:
cloud theory cloud transformation region growing image segmentation
分类号:
TP391
DOI:
10.3969/j.issn.1009-671X.2010.03.012
文献标志码:
A
摘要:
针对区域生长算法的种子点初始化和生长准则问题,提出了一种基于云模型和区域生长的图像分割方法.该方法首先利用云变换对图像进行变换生成云模型,然后利用云模型的Ex作为区域生长的种子点,以云的极大判定法则作为区域生长准则进行区域生长,获得最终的分割结果.这种分割方法不但克服了区域生长法种子点和生长准则选取不当而产生过分割和欠分割的不足,而且很大地提高了云模型分割图片的速度,实验结果证明,该方法可以准确地分割出目标,是一种有效的图像分割方法.
Abstract:
:A segmentation algorithm based on the cloud model and the region growing theory is proposed. First, an image is transformed to a cloud model by cloud transformation, and then, the cloud grows regionally, taking Ex of the cloud model as the seed of region growing and enormous determination principle as the criteria of regional growing. In the end the final segmentation result can be got. This segmentation method can not only overcome excessive or less segmentation due to improper selection of seeds and the region growing principle, but also greatly enhance the speed of image segmentation in the cloud mode segmentation. Experimental result proves that this method can exactly segment the goal from the image and it is an effective image segmentation method.

参考文献/References:

[1]章毓晋.图像分割[M]. 北京:科学出版社,2001:10-20.
[2]陈方昕. 基于区域生长法的图像分割技术[J]. 科技信息, 2008(15):58-59.
[3]秦 昆,李德毅,许 凯.基于云模型的图像分割研究[J].测量信息与工程,2006,31(5):3-5.
[4]邸凯昌.空间数据发掘与知识发现[M].武汉:武汉大学出社,2001:1-121.
[5]李德毅,杜 鸧.不确定性人工智能[M].北京:国防工业出版社,2005:5-40.
[6]YANG X M,YUAN J S,MAO H N,et al. A novel based time series predictive method for middle term cloud theory electri load forecasting[C]// IMACS Multi-Conference on CESA October. Beijing,China,2006:4-6.
[7]XU Kai,QIN Kun,LI Deren. New method of cloud synthesis and application in image segmentation[C]// MIPPR2007:Automatic Target Recognition and Image Analysis;and MultisPectral Image Acquisition. Wuhan,China,2007:6786.
[8]LI Jing,LI Lingling,WAN Juan,et al. The modeling method for nonintrusive objective speech quality measurement based on cloud theory [C]// CCC 2007. Hunan,China,2007:324 -327.
[9]秦 昆,徐 敏. 基于云模型和FCM聚类的遥感图像分割方法[J]. 地球信息科学,2008,10(3):324-327 .
[10]蒋 嵘,李德毅,范建华.数值型数据的泛概念树的自动生成方法[J]. 计算机学报,2000,23(5):470-476.

相似文献/References:

[1]李万臣,田淑娟.一种新的熵的提取方法在图像分割中的应用[J].应用科技,2013,40(05):48.[doi:10.3969/j.issn.1009-671X.201211014]
 LI Wanchen,TIAN Shujuan.Application of a new entropy extraction method in image segmentation[J].Applied science and technology,2013,40(03):48.[doi:10.3969/j.issn.1009-671X.201211014]

备注/Memo

备注/Memo:
作者简介:李万臣(1963- ),男,教授,主要研究方向:信号与信息处理,E-mail:lwchen@hrbeu.edu.cn.
更新日期/Last Update: 2010-04-08