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Phase congruency based retinal vessel segmentation

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

Abstract

Detection of blood vessels in a retinal fundus image is the preliminary step to diagnose several retinal diseases. There exist a number of methods to accomplish this task automatically. However, all of these methods suffer from lengthy processing time. The other major use of retina scanning is biometric authentication, for which a real time vessel detection system is required. In this work we describe a method that acquires binary vessel image from a color retinal fundus image in near real time. This method first generates the phase congruency image of the green channel of a color retinal image, and then thresholding is applied on the phase congruency image to obtain the blood vessels. Our method is able to acquire the blood vessels from a retinal fundus image within 10 seconds on a PC with the values of 'accuracy' and 'area under ROC: (0.92, 0.94) for the standard testing database called DRIVE. However, a (0.90, 0.91) accuracy and area under ROC can be acquired in less than 2 sec. © 2009 IEEE.
Original languageEnglish
Title of host publicationProceedings of the 2009 International Conference on Machine Learning and Cybernetics
Pages2458-2462
Volume4
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Machine Learning and Cybernetics - Baoding, China
Duration: 12 Jul 200915 Jul 2009

Publication series

Name
Volume4

Conference

Conference2009 International Conference on Machine Learning and Cybernetics
PlaceChina
CityBaoding
Period12/07/0915/07/09

Research Keywords

  • Blood-vessel detection
  • Fundus image
  • Log-Gabor wavelets
  • Phase congruency
  • Retina

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