Write a Matlab function to normalise a set of image points so their mean is zero and their root mean squared distance from the origin is √2. 

This was explained in the document I found as:

function [T_norm] = normalise_points(X); 
% normalise_points determines the homogeneous 
% transformation matrix T_norm such that 
% 
% X_norm = T_norm*X 
% 
% defines an X_norm with a mean of 0 and rms 
% (root mean squared) distance from the origin 
% of sqrt(2). 

[T1_norm] = normalise_points(X1); 
X1_norm = T1_norm*X1; 
[T2_norm] = normalise_points(X2); 
X2_norm = T2_norm*X2; 

I have also found some Matlab code (see below), that normalises an
array of homogenous, it doesn't quite do the same function as the previous mentioned -
I don't think it achieves the mean average of 0 and of course I don't have the homogeneous transformation matrix, which I think could be useful to me later now.

Anyhelp
modifying it in so I can achieve the said function would be greatly appreciated. 

% HNORMALISE - Normalises array of homogeneous coordinates to a scale of 1
%
% Usage: nx = hnormalise(x)
%
% Argument:
% x - an Nxnpts array of homogeneous coordinates.
%
% Returns:
% nx - an Nxnpts array of homogeneous coordinates rescaled so
% that the scale values nx(N,:) are all 1.
%
% Note that any homogeneous coordinates at infinity (having a scale value of
% 0) are left unchanged.

% Peter Kovesi 
% School of Computer Science & Software Engineering
% The University of Western Australia
% http://www.csse.uwa.edu.au/~pk
%
% February 2004

function nx = hnormalise(x)

[rows,npts] = size(x);
nx = x;

% Find the indices of the points that are not at infinity
finiteind = find(abs(x(rows,:)) > eps);

if length(finiteind) ~= npts
warning('Some points are at infinity');
end

% Normalise points not at infinity
for r = 1:rows-1
nx(r,finiteind) = x(r,finiteind)./x(rows,finiteind);
end
nx(rows,finiteind) = 1;