An evaluation of semi-automatic approaches to contour segmentation applied to fungal hyphae

Iain M. Inglis, Alison J. Gray

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Semiautomatic image analysis techniques are particularly useful in biological applications, which commonly generate very complex images, and offer considerable flexibility. However, systematic study of such methods is lacking; most research develops fully automatic algorithms. This paper describes a study to evaluate several different semiautomatic or computer-assisted approaches to contour segmentation within the context of segmenting degraded images of fungal hyphae. Four different types of contour segmentation method, with varying degrees and types of user input, are outlined and applied to hyphal images. The methods are evaluated both quantitatively and qualitatively by comparing results obtained by several test subjects segmenting simulated images qualitatively similar to the hyphal images of interest. An active contour model approach, using control points, emerges as the method to be preferred to three more traditional approaches. Feedback from the image provider indicates that any of the methods described have something useful to offer for segmentation of hyphae.
LanguageEnglish
Pages232-239
Number of pages7
JournalBiometrics
Volume57
Issue number1
DOIs
Publication statusPublished - Mar 2001

Fingerprint

Hyphae
Image analysis
hyphae
Segmentation
Feedback
Evaluation
methodology
Active Contour Model
Control Points
Image Analysis
Flexibility
image analysis
Research
Evaluate
testing

Keywords

  • edge detection
  • feature extraction
  • hyphae
  • image analysis
  • segmentation
  • semiautomatic methods
  • snakes
  • biology
  • biometrics

Cite this

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An evaluation of semi-automatic approaches to contour segmentation applied to fungal hyphae. / Inglis, Iain M.; Gray, Alison J.

In: Biometrics, Vol. 57, No. 1, 03.2001, p. 232-239.

Research output: Contribution to journalArticle

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