ihough.m

来自澳大利亚Qeensland大学的计算机视觉Matlab工具箱。 This Toolbox provides a number of functions that are useful in co

%IHOUGH	Hough transform
%
%	[H TH D] = IHOUGH(IM)
%	[H TH D] = IHOUGH(IM, Nd)
%	[H TH D] = IHOUGH(IM, Nd, Nth)
%
%	Compute the Hough transform of the image IM data.  Only non-zero pixels
%	increment the accumulator and the increment is the absolute value of 
%	the pixel value.
%
% 	The accumulator array has theta across the columns and offset down 
%	the rows.  Theta spans the range -pi/2 to pi/2 in Nth increments.
%	Offset is in the range 1 to number of rows of IM with Nd steps.
%	Both Nth and Nd default to 64.
%
%	Clipping is applied so that only those points lying within the Hough 
%	accumulator bounds are updated.
%
%	The output arguments TH and D give the theta and offset value vectors 
%	for the accumulator columns and rows respectively.  With no output 
%	arguments the Hough accumulator is displayed as a greyscale image.
% 
%	For this version of the Hough transform lines are described by
%
%		d = y cos(theta) + x sin(theta)
%
%	where theta is the angle the line makes to horizontal axis, and d is 
%	the perpendicular distance between (0,0) and the line.  A horizontal 
%	line has theta = 0, a vertical line has theta = pi/2 or -pi/2
%
% SEE ALSO: xyhough mkline, mksq, isobel ilap
%
%	Copyright (c) Peter Corke, 1999  Machine Vision Toolbox for Matlab


% 1995 Peter Corke

function [H,TH,D] = ihough(IM, Nd, Nth)

	nc = numcols(IM);
	nr = numrows(IM);

	if nargin < 3,
		Nth = 64;
	end
	if nargin < 2,
		Nd = 64;
	end

	IM = abs(IM);
	i = find(IM > 0) - 1;	% find the indices of each non-zero pixel
	x = floor(i/nr)+1;	% determine (x,y) coordinate
	y = rem(i, nr)+1;

	xyz = [x y IM(i+1)];
	switch nargout,
	case 0, xyhough(xyz, [1 nr Nd], Nth);
	case 1, H = xyhough(xyz, [1 nr Nd], Nth);
	case 2, [H,TH] = xyhough(xyz, [1 nr Nd], Nth);
	case 3, [H,TH,D] = xyhough(xyz, [1 nr Nd], Nth);
	end