i received an error tat: too many or too few input arguments.enter GLCM and pairs.How to overcome it

i received an error.. function definitions are not permitted at the prompt or in script.could u plss help me in removing this?

my coding is:

function [out] = MamoFeatures(glcmin,pairs)
% Features computed 
% Autocorrelation: [2]                      (out.autoc)
% Contrast: matlab/[1,2]                    (out.contr)
% Correlation: matlab                       (out.corrm)
% Correlation: [1,2]                        (out.corrp)
% Cluster Prominence: [2]                   (out.cprom)
% Cluster Shade: [2]                        (out.cshad)
% Dissimilarity: [2]                        (out.dissi)
% Energy: matlab / [1,2]                    (out.energ)
% Entropy: [2]                              (out.entro)
% Homogeneity: matlab                       (out.homom)
% Homogeneity: [2]                          (out.homop)
% Maximum probability: [2]                  (out.maxpr)
% Sum of sqaures: Variance [1]              (out.sosvh)
% Sum average [1]                           (out.savgh)
% Sum variance [1]                          (out.svarh)
% Sum entropy [1]                           (out.senth)
% Difference variance [1]                   (out.dvarh)
% Difference entropy [1]                    (out.denth)
% Information measure of correlation1 [1]   (out.inf1h)
% Informaiton measure of correlation2 [1]   (out.inf2h)
% Inverse difference (INV) is homom [3]     (out.homom)
% Inverse difference normalized (INN) [3]   (out.indnc) 
% Inverse difference moment normalized [3]  (out.idmnc)

% References:
% 1. R. M. Haralick, K. Shanmugam, and I. Dinstein, Textural Features of
% Image Classification, IEEE Transactions on Systems, Man and Cybernetics,
% vol. SMC-3, no. 6, Nov. 1973
% 2. L. Soh and C. Tsatsoulis, Texture Analysis of SAR Sea Ice Imagery
% Using Gray Level Co-Occurrence Matrices, IEEE Transactions on Geoscience
% and Remote Sensing, vol. 37, no. 2, March 1999.
% 3. D A. Clausi, An analysis of co-occurrence texture statistics as a
% function of grey level quantization, Can. J. Remote Sensing, vol. 28, no.
% 1, pp. 45-62, 2002
% 4. http://murphylab.web.cmu.edu/publications/boland/boland_node26.html
if ((nargin > 2) || (nargin == 0))
   error('Too many or too few input arguments. Enter GLCM and pairs.');
elseif ( (nargin == 2) ) 
    if ((size(glcmin,1) <= 1) || (size(glcmin,2) <= 1))
       error('The GLCM should be a 2-D or 3-D matrix.');
    elseif ( size(glcmin,1) ~= size(glcmin,2) )
        error('Each GLCM should be square with NumLevels rows and NumLevels cols');
    end    
elseif (nargin == 1) % only GLCM is entered
    pairs = 0; % default is numbers and input 1 for percentage
    if ((size(glcmin,1) <= 1) || (size(glcmin,2) <= 1))
       error('The GLCM should be a 2-D or 3-D matrix.');
    elseif ( size(glcmin,1) ~= size(glcmin,2) )
       error('Each GLCM should be square with NumLevels rows and NumLevels cols');
    end    
end

format long e
if (pairs == 1)
    newn = 1;
    for nglcm = 1:2:size(glcmin,3)
        glcm(:,:,newn)  = glcmin(:,:,nglcm) + glcmin(:,:,nglcm+1);
        newn = newn + 1;
    end
elseif (pairs == 0)
    glcm = glcmin;
end

size_glcm_1 = size(glcm,1);
size_glcm_2 = size(glcm,2);
size_glcm_3 = size(glcm,3);

% checked 
out.autoc = zeros(1,size_glcm_3); % Autocorrelation: [2] 
out.contr = zeros(1,size_glcm_3); % Contrast: matlab/[1,2]
out.corrm = zeros(1,size_glcm_3); % Correlation: matlab
out.corrp = zeros(1,size_glcm_3); % Correlation: [1,2]
out.cprom = zeros(1,size_glcm_3); % Cluster Prominence: [2]
out.cshad = zeros(1,size_glcm_3); % Cluster Shade: [2]
out.dissi = zeros(1,size_glcm_3); % Dissimilarity: [2]
out.energ = zeros(1,size_glcm_3); % Energy: matlab / [1,2]
out.entro = zeros(1,size_glcm_3); % Entropy: [2]
out.homom = zeros(1,size_glcm_3); % Homogeneity: matlab
out.homop = zeros(1,size_glcm_3); % Homogeneity: [2]
out.maxpr = zeros(1,size_glcm_3); % Maximum probability: [2]

out.sosvh = zeros(1,size_glcm_3); % Sum of sqaures: Variance [1]
out.savgh = zeros(1,size_glcm_3); % Sum average [1]
out.svarh = zeros(1,size_glcm_3); % Sum variance [1]
out.senth = zeros(1,size_glcm_3); % Sum entropy [1]
out.dvarh = zeros(1,size_glcm_3); % Difference variance [4]
%out.dvarh2 = zeros(1,size_glcm_3); % Difference variance [1]
out.denth = zeros(1,size_glcm_3); % Difference entropy [1]
out.inf1h = zeros(1,size_glcm_3); % Information measure of correlation1 [1]
out.inf2h = zeros(1,size_glcm_3); % Informaiton measure of correlation2 [1]
%out.mxcch = zeros(1,size_glcm_3);% maximal correlation coefficient [1]
%out.invdc = zeros(1,size_glcm_3);% Inverse difference (INV) is homom [3]
out.indnc = zeros(1,size_glcm_3); % Inverse difference normalized (INN) [3]
out.idmnc = zeros(1,size_glcm_3); % Inverse difference moment normalized [3]

glcm_sum  = zeros(size_glcm_3,1);
glcm_mean = zeros(size_glcm_3,1);
glcm_var  = zeros(size_glcm_3,1);

u_x = zeros(size_glcm_3,1);
u_y = zeros(size_glcm_3,1);
s_x = zeros(size_glcm_3,1);
s_y = zeros(size_glcm_3,1);

p_x = zeros(size_glcm_1,size_glcm_3);  
p_y = zeros(size_glcm_2,size_glcm_3); 
p_xplusy = zeros((size_glcm_1*2 - 1),size_glcm_3); 
p_xminusy = zeros((size_glcm_1),size_glcm_3); 

for k = 1:size_glcm_3 

      glcm_sum(k) = sum(sum(glcm(:,:,k)));
      glcm(:,:,k) = glcm(:,:,k)./glcm_sum(k); 
      glcm_mean(k) = mean2(glcm(:,:,k)); 
      glcm_var(k)  = (std2(glcm(:,:,k)))^2;

      for i = 1:size_glcm_1

          for j = 1:size_glcm_2

              out.contr(k) = out.contr(k) + (abs(i - j))^2.*glcm(i,j,k);
              out.dissi(k) = out.dissi(k) + (abs(i - j)*glcm(i,j,k));
              out.energ(k) = out.energ(k) + (glcm(i,j,k).^2);
              out.entro(k) = out.entro(k) - (glcm(i,j,k)*log(glcm(i,j,k) + eps));
              out.homom(k) = out.homom(k) + (glcm(i,j,k)/( 1 + abs(i-j) ));
              out.homop(k) = out.homop(k) + (glcm(i,j,k)/( 1 + (i - j)^2));
              out.sosvh(k) = out.sosvh(k) + glcm(i,j,k)*((i - glcm_mean(k))^2);
              out.indnc(k) = out.indnc(k) + (glcm(i,j,k)/( 1 + (abs(i-j)/size_glcm_1) ));
              out.idmnc(k) = out.idmnc(k) + (glcm(i,j,k)/( 1 + ((i - j)/size_glcm_1)^2));
              u_x(k)          = u_x(k) + (i)*glcm(i,j,k); 
              u_y(k)          = u_y(k) + (j)*glcm(i,j,k); 
          end

      end
      out.maxpr(k) = max(max(glcm(:,:,k)));
  end

for k = 1:size_glcm_3

      for i = 1:size_glcm_1

              end
          end
      end

end

for k = 1:(size_glcm_3)

      for i = 1:(2*(size_glcm_1)-1)
          out.savgh(k) = out.savgh(k) + (i+1)*p_xplusy(i,k);
          out.senth(k) = out.senth(k) - (p_xplusy(i,k)*log(p_xplusy(i,k) + eps));
      end

end

for k = 1:(size_glcm_3)

      for i = 1:(2*(size_glcm_1)-1)
          out.svarh(k) = out.svarh(k) + (((i+1) - out.senth(k))^2)*p_xplusy(i,k);
      end

end
end

for k = 1:size_glcm_3
    hxy(k) = out.entro(k);
    for i = 1:size_glcm_1

          for j = 1:size_glcm_2
              hxy1(k) = hxy1(k) - (glcm(i,j,k)*log(p_x(i,k)*p_y(j,k) + eps));
              hxy2(k) = hxy2(k) - (p_x(i,k)*p_y(j,k)*log(p_x(i,k)*p_y(j,k) + eps));
          end
          hx(k) = hx(k) - (p_x(i,k)*log(p_x(i,k) + eps));
          hy(k) = hy(k) - (p_y(i,k)*log(p_y(i,k) + eps));
      end
      out.inf1h(k) = ( hxy(k) - hxy1(k) ) / ( max([hx(k),hy(k)]) );
      out.inf2h(k) = ( 1 - exp( -2*( hxy2(k) - hxy(k) ) ) )^0.5;
  end

corm = zeros(size_glcm_3,1);
corp = zeros(size_glcm_3,1);
for k = 1:size_glcm_3
    for i = 1:size_glcm_1
        for j = 1:size_glcm_2
            s_x(k)  = s_x(k)  + (((i) - u_x(k))^2)*glcm(i,j,k);

              out.cprom(k) = out.cprom(k) + (((i + j - u_x(k) - u_y(k))^4)*...
                  glcm(i,j,k));
              out.cshad(k) = out.cshad(k) + (((i + j - u_x(k) - u_y(k))^3)*...
                  glcm(i,j,k));
          end
      end

      s_x(k) = s_x(k) ^ 0.5;
      s_y(k) = s_y(k) ^ 0.5;
      out.autoc(k) = corp(k);
      out.corrp(k) = (corp(k) - u_x(k)*u_y(k))/(s_x(k)*s_y(k));
      out.corrm(k) = corm(k) / (s_x(k)*s_y(k));
  end

[Honglei Chen]

Please format your code.

Answer 1

[Sean de Wolski]

Sure. Do not defined functions in a script or at the command line. What this means is if you have an *.m file and you want it to be a function, the first non-comment line needs to be

function

Answer 2

[Walter Roberson]

You need to write that code to the file MamoFeatures.m before you can use it.