Multiscale phase congruency analysis for image edge visual saliency detection

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

9 Citations (Scopus)

Abstract

A novel multiscale phase congruency (MPC) based analysis method is proposed in this paper for edge saliency detection and non-salient region texture suppression. Several MPC maps are proposed to be merged. Gaussian function based center priors and threshold processing are applied for the final edge saliency map generation, which can effectively suppress the textures and the detailed edges of non-salient regions. Experimental results show that the proposed MPC based edge saliency detection method can better generate edge saliency map for the most salient region in an image than the traditional PC based edge detection method and the other state-of-the-art saliency detection methods.
Original languageEnglish
Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
PublisherIEEE Computer Society
Pages75-80
Volume1
ISBN (Print)9781509003891
DOIs
Publication statusPublished - 21 Feb 2017
Event2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016 - Jeju Island, Korea, Republic of
Duration: 10 Jul 201613 Jul 2016

Publication series

Name
Volume1
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016
PlaceKorea, Republic of
CityJeju Island
Period10/07/1613/07/16

Research Keywords

  • Background texture suppression
  • Edge detection
  • Edge saliency map
  • Foreground extraction
  • Gaussian center priors
  • Multiscale analysis
  • Non-salient region suppression
  • Phase congruency
  • Salient object boundary
  • Visual attention
  • Visual saliency

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