Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/990
Title: A new image thresholding method based on Gaussian mixture model
Authors: Huang, ZK
Chau, KW 
Keywords: Histogram
Optimization
Thresholding
Issue Date: 15-Nov-2008
Publisher: Elsevier
Source: Applied mathematics and computation, 15 Nov. 2008, v. 205, no. 2, p. 899-907 How to cite?
Journal: Applied mathematics and computation 
Abstract: 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.
URI: http://hdl.handle.net/10397/990
ISSN: 0096-3003
EISSN: 1873-5649
DOI: 10.1016/j.amc.2008.05.130
Rights: Applied Mathematics and Computation © 2008 Published by Elsevier Inc. The journal web site is located at http://www.sciencedirect.com.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
AMC1.pdfPre-published version649.63 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents

SCOPUSTM   
Citations

114
Last Week
0
Last month
1
Citations as of Aug 13, 2018

WEB OF SCIENCETM
Citations

78
Last Week
0
Last month
2
Citations as of Aug 21, 2018

Page view(s)

491
Last Week
0
Last month
Citations as of Aug 14, 2018

Download(s)

7,111
Citations as of Aug 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.