Documentation>MATLAB API>MSER - vl_mser

R=VL_MSER(I) computes the Maximally Stable Extremal Regions (MSER) [1] of image I with stability threshold DELTA. I is any array of class UINT8. R is a vector of region seeds.

A (maximally stable) extremal region is just a connected component of one of the level sets of the image I. An extremal region can be recovered from a seed X as the connected component of the level set {Y: I(Y) <= I(X)} which contains the pixel o index X.

The function supports images of arbitrary dimension D.

[R,F]=VL_MSER(...) also returns ellipsoids F fitted to the regions. Each column of F describes an ellipsoid; F(1:D,i) is the center of the elliposid and F(D:end,i) are the independent elements of the co-variance matrix of the ellipsoid.

Ellipsoids are computed according to the same reference frame of I seen as a matrix. This means that the first coordinate spans the first dimension of I.

Notice that for 2-D images usually the opposite convention is used (i.e. the first coordinate is the x-axis, which corresponds to the column index). Thus, if the function VL_PLOTFRAME() is used to plot the ellipses, the frames F should be `transposed' as in F = F([2 1 5 4 3],:). VL_ERTR() exists for this purpose.

VL_MSER(I,'Option'[,Value]...) accepts the following options

Delta [5]

Set the DELTA parameter of the VL_MSER algorithm. Roughly speaking, the stability of a region is the relative variation of the region area when the intensity is changed of +/- Delta/2.

MaxArea [0.75]

Set the maximum area (volume) of the regions relative to the image domain area (volume).

MinArea [3 / numPixels]

Set the minimum area (volume) of the regions relative to the image domain area (volume).

MaxVariation [0.25]

Set the maximum variation (absolute stability score) of the regions.

MinDiversity [0.2]

Set the minimum diversity of the region. When the relative area variation of two nested regions is below this threshold, then only the most stable one is selected.

BrightOnDark [1]

Detect bright-on-dark MSERs. This corresponds to MSERs of the inverted image.

DarkOnBright [1]

Detect dark-on-bright MSERs. This corresponds to MSERs of the original image.


Be verbose.


[1] J. Matas, O. Chum, M. Urban, and T. Pajdla, "Robust wide baseline stereo from maximally stable extremal regions," in Proc. BMVC, 2002.

See also: VL_HELP().