I\'m trying to write a ridge detection algorithm, and all of the sources I\'ve found seem to conflate edge detection with ridge detection. Right now, I\'ve implemented the Canny
I was going to suggest cleaning up your lines like Ian said, but if you don't want to do that, you might also look into doing some variant of a hough transform.
http://en.wikipedia.org/wiki/Hough_transform
You should be able to get the actual equation for the line from this, so you can make it as thin or as thick as you like. The only tricky part is figuring out where the line ends.
Here's the code I wrote for a hough transform a few years ago, written in MATLAB. I'm not sure how well it works anymore, but it should give you a general idea. It will find all the lines (not segments) in an image
im = imread('cube.tif');
[bin1,bin2,bin3] = canny(im);
%% define constants
binary = bin1;
distStep = 10; % in pixels
angStep = 6; % in degrees
thresh = 50;
%% vote
maxDist = sqrt((size(binary,1))^2+(size(binary,2))^2);
angLoop = 0:angStep*pi/180:pi;
origin = size(binary)/2;
accum = zeros(ceil(maxDist/distStep)+1,ceil(360/angStep)+1);
for y=1:size(binary,2)
for x=1:size(binary,1)
if binary(x,y)
for t = angLoop
dx = x-origin(1);
dy = y-origin(2);
r = x*cos(t)+y*sin(t);
if r < 0
r = -r;
t = t + pi;
end
ri = round(r/distStep)+1;
ti = round(t*180/pi/angStep)+1;
accum(ri,ti) = accum(ri,ti)+1;
end
end
end
end
imagesc(accum);
%% find local maxima in accumulator
accumThresh = accum - thresh;
accumThresh(logical(accumThresh<0)) = 0;
accumMax = imregionalmax(accumThresh);
imagesc(accumMax);
%% calculate radius & angle of lines
dist = [];
ang = [];
for t=1:size(accumMax,2)
for r=1:size(accumMax,1)
if accumMax(r,t)
ang = [ang;(t-1)*angStep/180*pi];
dist = [dist;(r-1)*distStep];
end
end
end
scatter(ang,dist);