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Diffstat (limited to 'macros/cvMean.sci')
| -rw-r--r-- | macros/cvMean.sci | 217 |
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diff --git a/macros/cvMean.sci b/macros/cvMean.sci new file mode 100644 index 0000000..ce8318e --- /dev/null +++ b/macros/cvMean.sci @@ -0,0 +1,217 @@ +//*********************************************************************// +// Author : Asmita Bhar, Kevin George +//*********************************************************************// + +function [val] = cvMean(image, varargin) +// Finds mean values in an input +// +// Calling Sequence +// val = cvMean(image); +// val = cvMean(image, name, value,...); +// val = cvMean(image, name, value,c,r); (only when ROI Processing is true) +// +// Parameters +// image : Input image matrix +// Dimension (Output) : Dimension along which the function operates - Row, Column, All or Custom. Default : All +// CustomDimension (Optional) : The integer dimension over which the function calculates the mean. This value cannot exceed the number of dimensions in input. It applies only when 'Dimension' property is set to 'Custom'. Default : 1 +// ROIProcessing (Optional) : It applies only when 'Dimension' property is set to 'All'. It calculates the mean within a particular region of the image. Default : false +// c (Optional): vector of y-coordinates of vectices of a rectangle(ROI). Applicable only when 'ROIProcssing' is set to 'true'. +// r (Optional): vector of x-coordinates of vectices of a rectangle(ROI). Applicable only when 'ROIProcssing' is set to 'true'. +// val : Stores the mean value calculated +// +// Description +// The function calculates the mean value in a given image matrix. +// +// Examples +// //Load an image +// I = imread('peppers.png'); +// //Calculate the mean (default dimension is 'All') +// val = cvMean(I); +// //Calculate the mean when dimension is 'Row' +// val = cvMean(I,'Dimension','Row'); +// //Calculate the mean within a given ROI +// a = [0 100 100 0]; +// b = [0 0 100 100]; +// val = cvMean(I,'ROIProcessing','true',a,b); +// +// Authors +// Asmita Bhar +// Kevin George +// + [lhs,rhs] = argn(0); + if rhs<1 then + error(msprintf("Not enough input arguments")); + end + if rhs>9 then + error(msprintf("Too many input arguments")); + end + [iRows iCols]=size(image(1)) + iChannels = size(image) + + dimension = 'All'; + customDimension = 1; + roiProcessing = 'false'; + + flag1=0; + i=1; + while(i<rhs-1) + if strcmpi(varargin(i),'Dimension')==0 then + dimension = varargin(i+1) + if strcmpi(dimension,"Column") & strcmpi(dimension,"Row") &strcmpi(dimension,"All") & strcmpi(dimension,"Custom") then + error(msprintf(" wrong input argument #%d, Dimension not matched",i)) + end + i=i+2; + elseif strcmpi(varargin(i),'CustomDimension')==0 then + customDimension = varargin(i+1) + flag1=1; + i=i+2; + elseif strcmpi(varargin(i), 'ROIProcessing')==0 then + roiProcessing = varargin(i+1) + if(roiProcessing=='true') then + c = varargin(i+2); + r = varargin(i+3); + i=i+4; + else + i=i+2; + end + end + + end + + if (strcmpi(dimension,'Custom') & (flag1==1)) + error(msprintf("The CustomDimension property is not relevant in this configuration")); + end + + if (strcmpi(dimension,"All") & strcmpi(roiProcessing,'true')) + error(msprintf("ROI Property is not relevant in this configuration")); + end + + if(customDimension<1) + error(msprintf("CustomDimension must be greater than or equal to 1")); + end + + if(iChannels==1) then + if(customDimension>2) + error(msprintf("CustomDimension cannot be greater than the dimension of the input.")); + end + elseif(iChannels==3) then + if(customDimension>3) + error(msprintf("CustomDimension cannot be greater than the dimension of the input.")); + end + end + + if(iChannels==1) + I = double(image(1)); + elseif(iChannels==3) + I1 = double(image(1)); + I2 = double(image(2)); + I3 = double(image(3)); + end + + if(roiProcessing=='false') then + if (dimension=='All') then + if(iChannels==1) then + val = mean(I) + elseif (iChannels==3) then + val1 = mean(I1) + val2 = mean(I2) + val3 = mean(I3) + val = mean([val1 val2 val3]) + end + end + if (dimension=='Row') then + if(iChannels==1) then + val = mean(I,'c'); + elseif(iChannels==3) then + val1 = mean(I1,'c'); + val2 = mean(I2,'c'); + val3 = mean(I3,'c'); + val(:,:,1) = val1; + val(:,:,2) = val2; + val(:,:,3) = val3; + end + end + if (dimension=='Column') then + if(iChannels==1) then + val = mean(I,'r'); + elseif(iChannels==3) then + val1 = mean(I1,'r'); + val2 = mean(I2,'r'); + val3 = mean(I3,'r'); + val(:,:,1) = val1; + val(:,:,2) = val2; + val(:,:,3) = val3; + end + end + if (dimension=='Custom') then + if(iChannels==1) then + if(customDimension==1) then + val = mean(I,'r'); + elseif(customDimension==2) then + val = mean(I,'c'); + end + elseif(iChannels==3) then + if(customDimension==1) then + val1 = mean(I1,'r'); + val2 = mean(I2,'r'); + val3 = mean(I3,'r'); + val(:,:,1) = val1; + val(:,:,2) = val2; + val(:,:,3) = val3; + elseif(customDimension==2) then + val1 = mean(I1,'c'); + val2 = mean(I2,'c'); + val3 = mean(I3,'c'); + val(:,:,1) = val1; + val(:,:,2) = val2; + val(:,:,3) = val3; + elseif(customDimension==3) then + for i=1:iRows + for j=1:iCols + val(i,j)= mean([I1(i,j) I2(i,j) I3(i,j)]); + end + + end + end + end + end + end + if(roiProcessing=='true') then + I4 = roipoly(image,c,r); + out = I4; + output = find(out>0); + [rows cols] = size(out); + if(iChannels==1) + ROI = zeros(iRows,iCols); + for i=1:cols + ROI(output(i)) = image(1)(output(i)); + end + elseif(iChannels==3) + ROI1 = zeros(iRows,iCols); + ROI2 = zeros(iRows,iCols); + ROI3 = zeros(iRows,iCols); + for i=1:cols + ROI1(output(i)) = image(1)(output(i)); + ROI2(output(i)) = image(2)(output(i)); + ROI3(output(i)) = image(3)(output(i)); + end + ROI = list(ROI1,ROI2,ROI3); + end + if (dimension=='All') then + if(iChannels==1) then + a=ROI; + val = mean(a(find(a>0))); + elseif (iChannels==3) then + a=ROI(1); + b=ROI(2); + c=ROI(3); + val1 = mean(a(find(a>0))); + val2 = mean(b(find(b>0))); + val3 = mean(c(find(c>0))); + val = mean([val1 val2 val3]); + end + end + end + +endfunction + |