% NORMALISE2DPTS - normalises 2D homogeneous points
%
% Function translates and normalises a set of 2D homogeneous points 
% so that their centroid is at the origin and their mean distance from 
% the origin is sqrt(2).  This process typically improves the
% conditioning of any equations used to solve homographies, fundamental
% matrices etc.
%
% Usage:   [newpts, T] = normalise2dpts(pts)
%
% Argument:
%   pts -  3xN array of 2D homogeneous coordinates
%
% Returns:
%   newpts -  3xN array of transformed 2D homogeneous coordinates.  The
%             scaling parameter is normalised to 1 unless the point is at
%             infinity. 
%   T      -  The 3x3 transformation matrix, newpts = T*pts
%           
% If there are some points at infinity the normalisation transform
% is calculated using just the finite points.  Being a scaling and
% translating transform this will not affect the points at infinity.

% Peter Kovesi
% School of Computer Science & Software Engineering
% The University of Western Australia
% pk at csse uwa edu au
% http://www.csse.uwa.edu.au/~pk
%
% May 2003      - Original version
% February 2004 - Modified to deal with points at infinity.
% December 2008 - meandist calculation modified to work with Octave 3.0.1
%                 (thanks to Ron Parr)
% December 2016 - Disabled warning messgae for points at infinity.


function [newpts, T] = normalise2dpts(pts)

    if size(pts,1) ~= 3
        error('pts must be 3xN');
    end
    
    % Find the indices of the points that are not at infinity
    finiteind = find(abs(pts(3,:)) > eps);
    
%    if length(finiteind) ~= size(pts,2)
%        warning('Some points are at infinity');
%    end
    
    % For the finite points ensure homogeneous coords have scale of 1
    pts(1,finiteind) = pts(1,finiteind)./pts(3,finiteind);
    pts(2,finiteind) = pts(2,finiteind)./pts(3,finiteind);
    pts(3,finiteind) = 1;
    
    c = mean(pts(1:2,finiteind)')';            % Centroid of finite points
    newp(1,finiteind) = pts(1,finiteind)-c(1); % Shift origin to centroid.
    newp(2,finiteind) = pts(2,finiteind)-c(2);
    
    dist = sqrt(newp(1,finiteind).^2 + newp(2,finiteind).^2);
    meandist = mean(dist(:));  % Ensure dist is a column vector for Octave 3.0.1
    
    scale = sqrt(2)/meandist;
    
    T = [scale   0   -scale*c(1)
         0     scale -scale*c(2)
         0       0      1      ];
    
    newpts = T*pts;
    
    
    