A human visual system-driven image segmentation algorithm

Renbin Peng, Pramod K. Varshney

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

This paper presents a novel image segmentation algorithm driven by human visual system (HVS) properties. Segmentation quality metrics, based on perceptual properties of HVS with respect to segmentation, are integrated into an energy function. The energy function encodes the HVS properties from both region-based and boundary-based perspectives, where the just-noticeable difference (JND) model is employed when calculating the difference between the image contents. Extensive experiments are carried out to compare the performances of three variations of the presented algorithm and several representative segmentation and clustering algorithms available in the literature. The results show superior performance of our approach.

Original languageEnglish (US)
Pages (from-to)66-79
Number of pages14
JournalJournal of Visual Communication and Image Representation
Volume26
DOIs
StatePublished - Jan 2015

Keywords

  • Boundary- and region-based segmentation
  • HVS-driven segmentation
  • Human visual system
  • Image processing
  • Image segmentation
  • Just-noticeable difference (JND) model
  • Markov random fields
  • Quality metrics

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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