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Centroid estimation based on MSER detection and Gaussian Mixture Model

  • Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

This paper proposes a sub-pixel centroid estimation algorithm for star field image recorded by CCD sensor. To handle the connected as well as partially overlapped star spots in a star region, we involve the the MSER (Maximally Stable Extremal Region) detector to discover the star spots and related characteristics of latent star spots in a star region. After extracting the star regions, we will estimate the locations of centroids in each star region simultaneously using the GMM (Gaussian Mixture Model) and Expectation-maximization (EM) algorithm, instead of segment each star spots in a star region. Using our algorithm, overlapped star spots can be discovered easily and their centroids can also be estimated effectively. Experiments on simulation data sets demonstrate effectiveness and robustness of this algorithm.

Original languageEnglish
Title of host publicationICSP 2014 - 2014 IEEE 12th International Conference on Signal Processing, Proceedings
EditorsBaozong Yuan, Qiuqi Ruan, Xiaofang Tang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages774-779
Number of pages6
EditionOctober
ISBN (Electronic)9781479921881
DOIs
StatePublished - 2014
Event12th IEEE International Conference on Signal Processing, ICSP 2014 - Hangzhou, China
Duration: 19 Oct 201423 Oct 2014

Publication series

NameInternational Conference on Signal Processing Proceedings, ICSP
NumberOctober
Volume2015-January
ISSN (Print)2164-5221
ISSN (Electronic)2164-523X

Conference

Conference12th IEEE International Conference on Signal Processing, ICSP 2014
Country/TerritoryChina
CityHangzhou
Period19/10/1423/10/14

Keywords

  • GMM
  • MSER
  • Star field image processing
  • Sub-pixel centroid estimation

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