📄 bwnoisereduction.m
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function Iout = bwNoiseReduction(IBW,n,NUM)
%--------------------------------------------------------------------------
% bwNoiseReduction - Reduce noise in Binary Image
%--------------------------------------------------------------------------
%Comments:
%
% This function gets the binary image and according to connectivity
% labeld the objects in Image and through the numbers of pixels in each
% connected component determined wether oject is noise or not.
%
%--------------------------------------------------------------------------
%Usage:
% Iout = bwNoiseReduction(IBW,n,NUM)
%--------------------------------------------------------------------------
%
%Arguments:
% IBW - a binary image. backgroung pixels have zerro value and
% forground and noisy objects have one value.
% n - n can have a value of either 4 or 8, where 4 specifies
% 4-connected objects and 8 specifies 8-connected objects; if the
% argument is omitted, it defaults to 8.
% NUM - Threshould number of object's pixels in binary image
% consider as noise
%
%Return:
% Iout - a biary image.
%--------------------------------------------------------------------------
%Written by:
% Javad Razjouyan
% Biomedical Engieering Department, Faculty of Engineering
% University of Shahed,Iran
% Javad_Razjouyan@yahoo.com
%
%July 3,2006 - Original Version
%--------------------------------------------------------------------------
%
%
%Set default values
if nargin == 1
n = 8;
NUM = 10;
elseif nargin == 2
NUM = 10;
end
%--------------------------------------------------------------------------
% Labeling the Input BW Image
%--------------------------------------------------------------------------
[L,obj] = bwlabel(IBW,n);
%--------------------------------------------------------------------------
% main process start here
%--------------------------------------------------------------------------
Iout = IBW;
for i=1:obj
fbw = find(L==i);
if length(fbw) < NUM
Iout(fbw) = 0;
end
end
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