Automatic thresholding from the gradients of region boundaries

G. Landini*, D. A. Randell, S. Fouad, A. Galton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We present an approach for automatic threshold segmentation of greyscale images. The procedure is inspired by a reinterpretation of the strategy observed in human operators when adjusting thresholds manually and interactively by means of ‘slider’ controls. The approach translates into two methods. The first one is suitable for single or multiple global thresholds to be applied globally to images and consists of searching for a threshold value that generates a phase whose boundary coincides with the largest gradients in the original image. The second method is a variation, implemented to operate on the discrete connected components of the thresholded phase (i.e. the binary regions) independently. Consequently, this becomes an adaptive local threshold procedure, which operates relative to regions, rather than to local image subsets as is the case in most local thresholding methods previously published. Adding constraints for specifying certain classes of expected objects in the images can improve the output of the method over the traditional ‘segmenting first, then classify’ approach.

Original languageEnglish
Pages (from-to)185-195
Number of pages11
JournalJournal of Microscopy
Volume265
Issue number2
Early online date20 Sep 2016
DOIs
Publication statusPublished - 1 Feb 2017

Bibliographical note

Funding: The research reported in this paper was supported by the Engineering and Physical Sciences Research Council (EPSRC), UK through funding under grant EP/M023869/1 ‘Novel context-based segmentation algorithms for intelligent microscopy’.

Keywords

  • Image processing
  • mathematical morphology
  • segmentation

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