Home > freetb4matlab > image > houghtf.m

houghtf

PURPOSE ^

% Perform the Hough transform for lines or circles.

SYNOPSIS ^

function [accum, R] = houghtf(bw, varargin)

DESCRIPTION ^

% -*- texinfo -*-
% @deftypefn {Function File} @var{H} = houghtf (@var{bw})
% @deftypefnx{Function File} @var{H} = houghtf (@var{bw}, @var{method})
% @deftypefnx{Function File} @var{H} = houghtf (@var{bw}, @var{method}, @var{arg})
% Perform the Hough transform for lines or circles.
%
% The @var{method} argument chooses between the Hough transform for lines and
% circles. It can be either 'line' (default) or 'circle'.
%
% @strong{Line Detection}
%
% If @var{method} is 'line', the function will compute the Hough transform for
% lines. A line is parametrised in @var{r} and @var{theta} as
% @example
% @var{r} = x*cos(@var{theta}) + y*sin(@var{theta}),
% @end example
% where @var{r} is distance between the line and the origin, while @var{theta}
% is the angle of the vector from the origin to this closest point. The result
% @var{H} is an @var{N} by @var{M} matrix containing the Hough transform. Here,
% @var{N} is the number different values of @var{r} that has been attempted.
% This is computed as @code{2*diag_length - 1}, where @code{diag_length} is
% the length of the diagonal of the input image. @var{M} is the number of
% different values of @var{theta}. These can be set through the third input
% argument @var{arg}. This must be a vector of real numbers, and is by default
% @code{pi*(-90:90)/180}.
%
% @strong{Circle Detection}
%
% If @var{method} is 'circle' the function will compute the Hough transform for
% circles. The circles are parametrised in @var{r} which denotes the radius of
% the circle. The third input argument @var{arg} must be a real vector containing
% the possible values of @var{r}.
% If the input image is @var{N} by @var{M}, then the result @var{H} will be an
% @var{N} by @var{M} by @var{K} array, where @var{K} denotes the number of
% different values of @var{r}.
%
% As an example, the following shows how to compute the Hough transform for circles
% with radius 3 or 7 in the image @var{im}
% @example
% bw = edge(im);
% H = houghtf(bw, 'circle', [3, 7]);
% @end example
% Here @var{H} will be an NxMx2 array, where @var{H}(:,:,1) will contain the
% Hough transform for circles with radius 3, and @var{H}(:,:,2) for radius 7.
% To find good circles you now need to find local maximas in @var{H}. If you
% find a local maxima in @var{H}(row, col, 1) it means that a good circle exists
% with center (row,col) and radius 3. One way to locate maximas is to use the
% @code{immaximas} function.
%
% @seealso{hough_line, hough_circle, immaximas}
% @end deftypefn

CROSS-REFERENCE INFORMATION ^

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