Edge and line oriented contour detection: State of the art

Giuseppe Papari*, Nicolai Petkov

*Corresponding author for this work

Research output: Contribution to journalArticleAcademic

247 Citations (Scopus)

Abstract

We present an overview of various edge and line oriented approaches to contour detection that have been proposed in the last two decades. By edge and line oriented we mean methods that do not rely on segmentation. Distinction is made between edges and contours. Contour detectors are divided in local and global operators. The former are mainly based on differential analysis, statistical approaches, phase congruency, rank order filters, and combinations thereof. The latter include computation of contour saliency, perceptual grouping, relaxation labeling and active contours. Important aspects are covered, such as preprocessing aimed to suppress texture and noise, multiresolution techniques, connections between computational models and properties of the human visual system, and use of shape priors. An overview of procedures and metrics for quantitative performance evaluation is also presented. Our main conclusion is that contour detection has reached high degree of sophistication, taking into account multimodal contour definition (by luminance, color or texture changes), mechanisms for reducing the contour masking influence of noise and texture, perceptual grouping, multiscale aspects and high-level vision information. (C) 2010 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)79-103
Number of pages25
JournalImage and vision computing
Volume29
Issue number2-3
DOIs
Publication statusPublished - Feb-2011

Keywords

  • Contour detection
  • Preprocessing
  • Local pattern analysis
  • Contour salience
  • Gestalt grouping
  • Closure
  • Scale-space
  • Performance evaluation
  • RELAXATION LABELING PROCESSES
  • IMAGE SEGMENTATION TECHNIQUES
  • RECEPTIVE-FIELD INHIBITION
  • GEODESIC ACTIVE CONTOURS
  • MONOGENIC SCALE-SPACE
  • PRIMARY VISUAL-CORTEX
  • GRADIENT VECTOR FLOW
  • ILL-POSED PROBLEMS
  • LEVEL SET METHODS
  • PERCEPTUAL ORGANIZATION

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