ColorED: Color edge and segment detection by Edge Drawing (ED)

Cuneyt Akinlar*, Cihan Topal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

We extend our recent edge and segment detector, Edge Drawing (GrayED), to detect edge segments in color images. Edge Drawing for color images, named ColorED, takes in a color image, and outputs a set of edge segments, each a contiguous, 1-pixel wide chain of pixels. Detected edge segments are then passed through an ‘a contrario’ validation step due to the Helmholtz principle to eliminate perceptually invalid detections. We quantitatively evaluate ColorED with different colorspaces and vector gradient operators within the precision-recall framework of the widely-used Berkeley Segmentation Dataset and Benchmark (BSDS300), and compare its results with those of GrayED and a color version of the Canny edge detector named ColorCanny. We conclude that color edge detection is in general superior to grayscale edge detection, and that ColorED with edge segment validation (ColorEDV) greatly outperforms GrayED, ColorED, and ColorCanny, producing an F-score of 0.6593 with DiZenzo and 0.6747 with the Compass operator while taking an average time of 31.5 ms for BSDS300.

Original languageEnglish
Pages (from-to)82-94
Number of pages13
JournalJournal of Visual Communication and Image Representation
Volume44
DOIs
Publication statusPublished - 1 Apr 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Inc.

Keywords

  • Color edge detection
  • Compass
  • Edge Drawing (ED)
  • Edge segment validation
  • Helmholtz principle
  • Vector gradient operators

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