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fix: Add vote accumulation logic to hough_transform_polar.m #31

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fix: Add vote accumulation logic to hough_transform_polar.m #31

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110 changes: 61 additions & 49 deletions matlab/hough_transform_polar.m
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Original file line number Diff line number Diff line change
@@ -1,50 +1,62 @@
function [r, theta] = hough_transform_polar(edge_map)

%% find x, y position from edge map
[edge_y, edge_x] = find(edge_map);

%% range of r
H = size(edge_map, 1);
W = size(edge_map, 2);

r_max = round(sqrt(H^2 + W^2));
r_min = -r_max;
r_step = 1;
r_range = r_min : r_step : r_max;

%% range of theta
theta_step = 0.01;
theta_range = -pi/2 : theta_step : pi/2;

%% create vote matrix
V = zeros(length(r_range), length(theta_range));

%% TODO: add votes
% V(1, 1) = 1; % remove this line
for i = 1:length(edge_y)
x = edge_x(i);
y = edge_y(i);
for theta_index = 1:length(theta_range)
theta = theta_range(theta_index);
r = x * cos(theta) + y * sin(theta);
if r_min <= r
if r <= r_max
r_index = round((r - r_min) / r_step) + 1;
V(r_index, theta_index) = V(r_index, theta_index) + 1;
end
end
end
end



%% visualize votes
% figure, imagesc(V); xlabel('theta'); ylabel('r');

%% find the maximal vote
max_vote = max(V(:));
[max_r_index, max_theta_index] = find( V == max_vote );
r = r_range(max_r_index);
theta = theta_range(max_theta_index);

function [r, theta] = hough_transform_polar(edge_map)
% HOUGH_TRANSFORM_POLAR Performs the Hough Transform to detect lines using polar coordinates.
%
% [r, theta] = HOUGH_TRANSFORM_POLAR(edge_map) takes a binary edge map image as input
% and returns the distance from the origin (r) and angle (theta) of the most prominent line
% detected in the image.
%
% Inputs:
% edge_map - A binary matrix representing the edge map of an image,
% where non-zero values indicate edge pixels.
%
% Outputs:
% r - The distance from the origin to the detected line.
% theta - The angle of the normal to the detected line.

%% find x, y position from edge map
[edge_y, edge_x] = find(edge_map);

%% range of r
H = size(edge_map, 1);
W = size(edge_map, 2);

r_max = round(sqrt(H^2 + W^2));
r_min = -r_max;
r_step = 1;
r_range = r_min : r_step : r_max;

%% range of theta
theta_step = 0.01;
theta_range = -pi/2 : theta_step : pi/2;

%% create vote matrix
V = zeros(length(r_range), length(theta_range));

%% add votes
for i = 1:length(edge_y)
x = edge_x(i);
y = edge_y(i);
for theta_index = 1:length(theta_range)
theta = theta_range(theta_index);
r = x * cos(theta) + y * sin(theta);
if r_min <= r
if r <= r_max
r_index = round((r - r_min) / r_step) + 1;
V(r_index, theta_index) = V(r_index, theta_index) + 1;
end
end
end
end



%% visualize votes
% figure, imagesc(V); xlabel('theta'); ylabel('r');

%% find the maximal vote
max_vote = max(V(:));
[max_r_index, max_theta_index] = find( V == max_vote );
r = r_range(max_r_index);
theta = theta_range(max_theta_index);

end