A new image thresholding method based on Gaussian mixture model

被引：147
|
作者：
Huang, Zhi-Kai [1 ,3 ]
Chau, Kwok-Wing [2 ]
机构：
[1] Chinese Acad Sci, Hefei Inst Intelligent Machines, Intelligent Comp Lab, POB 1130, Hefei 230031, Anhui, Peoples R China
[2] Hong Kong Polytech Univ, Dept Civil & Struct Engn, Hong Kong, Hong Kong, Peoples R China
[3] Nanchang Inst Technol, Dept Machinery & Dynam Engn, Nanchang 330099, Jiangxi, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2008年 / 205卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Histogram; Optimization; Thresholding;
D O I：
10.1016/j.amc.2008.05.130
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, an efficient approach to search for the global threshold of image using Gaussian mixture model is proposed. Firstly, a gray-level histogram of an image is represented as a function of the frequencies of gray-level. Then to fit the Gaussian mixtures to the histogram of image, the expectation maximization (EM) algorithm is developed to estimate the number of Gaussian mixture of such histograms and their corresponding parameterization. Finally, the optimal threshold which is the average of these Gaussian mixture means is chosen. And the experimental results show that the new algorithm performs better. (C) 2008 Published by Elsevier Inc.
引用
收藏
页码：899 / 907
页数：9
相关论文
共 50 条
  • [1] An image thresholding approach based on Gaussian mixture model
    Zhao, Like
    Zheng, Shunyi
    Yang, Wenjing
    Wei, Haitao
    Huang, Xia
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2019, 22 (01) : 75 - 88
  • [2] An image thresholding approach based on Gaussian mixture model
    Like Zhao
    Shunyi Zheng
    Wenjing Yang
    Haitao Wei
    Xia Huang
    [J]. Pattern Analysis and Applications, 2019, 22 : 75 - 88
  • [3] An airborne image stabilization method based on the Gaussian mixture model
    Hongbin Deng
    Yunde Jia
    Yihua Xu
    Wei Liang
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8, 2007, : 2488 - 2492
  • [4] A novel image-denosing method based on the mixture gaussian model
    Long, XM
    Jing, Z
    [J]. WAVELET ANALYSIS AND ACTIVE MEDIA TECHNOLOGY VOLS 1-3, 2005, : 1295 - 1300
  • [5] An airborne image stabilization method based on projection and the Gaussian mixture model
    Deng, Hong-Bin
    Jia, Yun-De
    Xu, Yi-Hua
    Liang, We
    [J]. PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 345 - 349
  • [6] Image thresholding using a novel estimation method in generalized Gaussian distribution mixture modeling
    Fan, Shu-Kai S.
    Lin, Yen
    Wu, Chia-Chan
    [J]. NEUROCOMPUTING, 2008, 72 (1-3) : 500 - 512
  • [7] Regularization Parameter Selection for Gaussian Mixture Model Based Image Denoising Method
    Zhang, J. W.
    Liu, J.
    Zheng, Y. H.
    Wang, J.
    [J]. ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING, 2017, 421 : 291 - 297
  • [8] A Vectorial Image Classification Method Based On Neighborhood Weighted Gaussian Mixture Model
    Tang, Hui
    Dillenseger, Jean-Louis
    Luo, Li Min
    [J]. 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8, 2008, : 1922 - +
  • [9] A GAUSSIAN MIXTURE MODEL-BASED REGULARIZATION METHOD IN ADAPTIVE IMAGE RESTORATION
    Liu Peng Zhang Yan Mao Zhigang (Shenzhen Graduate School
    [J]. Journal of Electronics(China), 2007, (01) : 83 - 89
  • [10] Image Similarity in Gaussian Mixture Model Based Image Retrieval
    Luszczkiewicz-Piatek, Maria
    [J]. IMAGE PROCESSING AND COMMUNICATIONS CHALLENGES 8, 2017, 525 : 87 - 95
12345