The strategy in this paper has been to
use a technique which is simple in the sense that a global thresholding algorithm is iterated over a subset of
current objects according to as few, simple and powerful rules as possible. The global thresholding algorithm
is hence, just a building block in an iteration process
which avoids complexities such as interpolation and
window size selection which feature in many adaptive
thresholding techniques (Chow and Kaneko, 1972;
Pe rez and Gonzalez, 1987; Tseng and Huang, 1993;
Yang et al., 1994). The domain of images for which
the thresholding technique is suitable, is, generally
speaking, those where the background, although variable, is locally brighter than the objects to be identi®ed, in this instance, particles or clusters of particles.
When designing the thresholding algorithm, special
care was taken to choose, as a building block, a global
The strategy in this paper has been touse a technique which is simple in the sense that a global thresholding algorithm is iterated over a subset ofcurrent objects according to as few, simple and powerful rules as possible. The global thresholding algorithmis hence, just a building block in an iteration processwhich avoids complexities such as interpolation andwindow size selection which feature in many adaptivethresholding techniques (Chow and Kaneko, 1972;Pe rez and Gonzalez, 1987; Tseng and Huang, 1993;Yang et al., 1994). The domain of images for whichthe thresholding technique is suitable, is, generallyspeaking, those where the background, although variable, is locally brighter than the objects to be identi®ed, in this instance, particles or clusters of particles.When designing the thresholding algorithm, specialcare was taken to choose, as a building block, a global
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