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vl_mser.m
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vl_mser.m
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% VL_MSER Maximally Stable Extremal Regions
% 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.
%
% Verbose::
% Be verbose.
%
% REFERENCES::
% [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().
% AUTORIGHTS
% Copyright (C) 2007-10 Andrea Vedaldi and Brian Fulkerson
%
% This file is part of VLFeat, available under the terms of the
% GNU GPLv2, or (at your option) any later version.