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A Coutour Detection Model Based on Surround Inhibition with Multiple Cues

  • Kaifu Yang
  • Yongjie Li
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 321)

Abstract

Sufficient physiological studies have revealed that surround inhibition substantially occurs when difference exists between the classical receptive field (CRF) and its surrounding (i.e. non-CRF) of most neurons in primary visual cortex (V1) for any local visual features. In this paper, we propose an improved contour detection model based on the biologically-plausible computational steps with non-CRF inhibition (also called surround inhibition) in V1. Through principal component analysis (PCA) we combine multiple local cues, including orientation, luminance and contrast, to improve contour detection in natural images. The results on a commonly used large image dataset demonstrate that surround inhibition combining multiple local cues can remarkably improve contour detection in complex scenes.

Keywords

contour detection surround inhibition receptive filed multiple local cues V1 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kaifu Yang
    • 1
  • Yongjie Li
    • 1
  1. 1.Key Laboratory for Neuroinformation of Ministry of EducationUniversity of Electronic Science and Technology of ChinaChengduChina

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