Maximally stable extremal regions (MSER)

MSER are a method for blob detection originally introduced by Matas et al. (64). The basic idea behind MSER is the following. Imagine we binarize a greyscale image with a variable threshold; as the threshold varies within a given range (let ∆ be the range) there will be some connected components of the binarized image that will remain approximately the same: these are stable regions. Among them, maximally stable regions are those exhibiting the lowest area variation when the threshold varies. A stable region is also extremal if the intensity of all its pixels is either higher (bright extremal regions) or lower (dark extremal regions) than that of the surrounding pixels.

In the experiments the value of ∆ was determined through grid search over ∆ ∈ {2, 4, 6, 8}, which returned ∆=2 as the optimal value. The other parameters were: minimum (maximum) area cut-off value for the detected blobs =10 px (25% of the area of the input image), maximum variation (absolute stability score) of the regions =0.25 and minimum diversity =0.2 (when the relative area difference between two nested regions was below this threshold only the most stable one was retained).