Application of Improved Genetic K-Means Clustering Algorithm in Image Segmentation

被引：1
|
作者：
Tan, Zhicun [1 ]
Lu, Ruihua [1 ]
机构：
[1] Southwest Univ, Inst Signal & Informat Proc, Chongqing 400715, Peoples R China
来源：
PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II | 2009年
关键词：
genetic K-means clustering algorithm; image segmentation; object function; algorithm optimization;
D O I：
10.1109/ETCS.2009.400
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
An improved genetic K-means clustering algorithm is proposed and is applied to image segmentation. According to the characteristics of the image, the feature vector of the pixel is properly chosen and the weight factors of the feature vector are adjusted, which enhances the segmentation precision. The selection of conventional genetic algorithm and the modification of mutation operations improve the speed of convergence. Computing time is reduced due to combining the membership matrix with the coding of chromosomes skillfully. The results of the experiments demonstrate that in the image segmentation the proposed algorithm is better than traditional genetic K-means algorithm.
引用
收藏
页码：625 / 628
页数：4
相关论文
共 50 条
  • [1] An improved K-means clustering algorithm in agricultural image segmentation
    Cheng, Huifeng
    Peng, Hui
    Liu, Shanmei
    [J]. PIAGENG 2013: IMAGE PROCESSING AND PHOTONICS FOR AGRICULTURAL ENGINEERING, 2013, 8761
  • [2] An improved K-means clustering algorithm for fish image segmentation
    Yao, Hong
    Duan, Qingling
    Li, Daoliang
    Wang, Jianping
    [J]. MATHEMATICAL AND COMPUTER MODELLING, 2013, 58 (3-4) : 784 - 792
  • [3] Application of Improved K-means Clustering Algorithm in Customer Segmentation
    Li, Gang
    [J]. INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY II, PTS 1-4, 2013, 411-414 : 1081 - 1084
  • [4] Medical image segmentation using K-MEANS clustering and improved watershed algorithm
    Ng, H. P.
    Ong, S. H.
    Foong, K. W. C.
    Goh, P. S.
    Nowinski, W. L.
    [J]. 7TH IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION, 2006, : 61 - +
  • [5] Image Segmentation using K-means Clustering Algorithm and Subtractive Clustering Algorithm
    Dhanachandra, Nameirakpam
    Manglem, Khumanthem
    Chanu, Yambem Jina
    [J]. ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015, 2015, 54 : 764 - 771
  • [6] Research on k-means Clustering Algorithm An Improved k-means Clustering Algorithm
    Shi Na
    Liu Xumin
    Guan Yong
    [J]. 2010 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY AND SECURITY INFORMATICS (IITSI 2010), 2010, : 63 - 67
  • [7] An improved genetic k-means algorithm for optimal clustering
    Guo, Hai-Xiang
    Zhu, Ke-Jun
    Gao, Si-Wei
    Liu, Ting
    [J]. ICDM 2006: SIXTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, WORKSHOPS, 2006, : 793 - +
  • [8] An Improved Genetic K-Means Algorithm for Spatial Clustering
    Wang, Yuanni
    Ge, Fei
    [J]. PROGRESS IN INTELLIGENCE COMPUTATION AND APPLICATIONS, 2008, : 123 - 126
  • [9] Optimized K-means (OKM) clustering algorithm for image segmentation
    Siddiqui, F. U.
    Isa, N. A. Mat
    [J]. OPTO-ELECTRONICS REVIEW, 2012, 20 (03) : 216 - 225
  • [10] Standard and Genetic k-means Clustering Techniques in Image Segmentation
    Malyszko, Dariusz
    Wierzchon, Slawomir T.
    [J]. 6TH INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT APPLICATIONS, PROCEEDINGS, 2007, : 299 - +
12345