Contour Detection by Multiresolution Surround Inhibition

Giuseppe Papari, Patrizio Campisi, Nicolai Petkov, Alessandro Neri

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

22 Citations (Scopus)
136 Downloads (Pure)

Abstract

In natural images, luminance changes occur both on object contours and on textures. Often, the latter are stronger than the former, thus standard edge detectors fail in isolating object contours from texture. To overcome this problem, we propose a multiresolution contour detector motivated by biological principles. At each scale, texture is suppressed by using a bipolar surround inhibition process. The binary contour map is obtained by a contour selection criterion that is more effective than the classical hysteresis thresholding. Robustness to noise is achieved by Bayesian gradient estimation.
Original languageEnglish
Title of host publication 2006 International Conference on Image Processing
PublisherIEEE
Pages749-752
Number of pages4
ISBN (Print)978-1-4244-0481-0
DOIs
Publication statusPublished - 2006
EventIEEE International Conference on Image Processing (ICIP 2006) - , Gabon
Duration: 8-Oct-200611-Oct-2006

Publication series

NameIEEE International Conference on Image Processing (ICIP)
PublisherIEEE
ISSN (Print)1522-4880

Other

OtherIEEE International Conference on Image Processing (ICIP 2006)
Country/TerritoryGabon
Period08/10/200611/10/2006

Keywords

  • edge
  • context
  • contour
  • surround suppression
  • texture
  • FIELD

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