Automatic thresholding from the gradients of region boundaries

Gabriel Landini, David Randell, Shereen Fouad, and Antony Galton

In Journal of Microscopy, Volume 235, No. 2, February 2017, pages 185-195.
DOI 10.1111/jmi.12474

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.

Early View online version (20th September 2016)

The work reported in this paper was funded by EPSRC grant EP/M023869/1, Novel context-based segmentation algorithms for intelligent microscopy

Antony Galton