CANNYEDGEPROD - Canny edge detection by scale multiplication.

Contents

Description

Two-scale Canny edge detection obtained by multiplication of Canny edge responses at two different scales following the approach of [BZW05].

Syntax

   edgemap = CANNYEDGEPROD(I, sigma2);
   [edgemap, mag, or] = CANNYEDGEPROD(I, sigma2, sigma1, ...
                                     'Property', propertyvalue, ...);

Inputs

I : input image

sigma2, sigma1 : standard-deviations of, resp., the coarsest and the finest Gaussian filters used for edge detection; default: sigma2 needs always to be passed as input and sigma1=1.

Property [propertyname propertyvalues]

'der' : string setting the name of the function used for edge detection; it can be: 'vista' (or 'matlab') or 'kovesi'; see function CANNYEDGEMAP; default: der='matlab'.

'c' : adjustment parameter used in [BZW05] for defining the threshold on the responses, see Sec.3.6; default: c=1.

'reduce' : logical value or string defining the way the different channels of a multispectral image into the edge map (see CANNYEDGE_BASE); it can be true or false, or one among 'igray', 'imax', 'gmax' or 'eor'; see CANNYEDGE_BASE and CANNYEDGE.

Outputs

edgemap : a binary edge map.

mag, or : optional output images storing the magnitude and the orientation of the gradient resp.

References

[Canny86] J.F. Canny: "A computational approach to edge detection", IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6):679-698, 1986. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4767851&tag=1

[BZW05] P. Bao, L. Zhang and X. Wu: "Canny edge detection enhancement by scale multiplication", IEEE Trans. on Image Processing, 27(9): 1485-1490, 2005. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1471712

See also

Ressembles: CANNYEDGE, CANNYEDGEMAP, EDGECORNER, ROTHWELLEDGE, CONGRUENCYEDGE, COMPASSEDGE, ANISOEDGE, ELDERZUCKEREDGE, SDGDEDGE, KOETHEDGE, PETROUEDGE. Requires: CANNYEDGEPROD_BASE.

Function implementation

function [edgemap, varargout] = cannyedgeprod(I, sig2, varargin)

parsing parameters

error(nargchk(2, 15, nargin, 'struct'));
error(nargoutchk(1, 3, nargout, 'struct'));

if ~isnumeric(I)
    error('cannyedgeprod:inputparameter','a matrix is required in input');
elseif ~isscalar(sig2) || sig2<0.05
    error('cannyedgeprod:inputparameter','invalid input parameter sigma');
end

p = createParser('CANNYEDGEPROD');   % create an instance of the inputParser class.
p.addOptional('sig1', 1., @(x)isscalar(x) && isfloat(x) && x>0.05);
% function handling the function used for estimating Canny edges
p.addParamValue('der', 'matlab', @(x)ischar(x) && ...
    any(strcmpi(x,{'vista','matlab','kovesi'})));
p.addParamValue('c', 1, @(x)isscalar(x) && x>=0);
p.addParamValue('reduce', false, @(x)islogical(x) || ...
    (ischar(x) && any(strcmpi(x,{'igray','imax','isum','gmax','eor'}))));

% parse and validate all input arguments
p.parse(varargin{:});
p = getvarParser(p);

check that the sigma variables are set properly, ie. that sig1<sig2, otherwise invert their roles for furhter processing

if p.sig1>sig2
    tmp = p.sig1; p.sig1 = sig2; sig2 = tmp;
elseif p.sig1==sig2
    p.sig1 =  sig2 - 0.05;
end;

main calculation

[edgemap, mag, or] = cannyedgeprod_base(I, sig2, p.sig1, p.der, p.c, p.reduce);

if nargout>=2, varargout{1} = mag;  end;
if nargout==3, varargout{2} = or;  end;

display

if p.disp
    figure, imagesc(edgemap), axis image off;
    if size(edgemap,3)==1, colormap gray;  end;
    title(['edge map product of scales \{' num2str(p.sig1) ':' num2str(sig2) '\}']);
end

end % end of cannyedgeprod