MATLAB: Return array of values between two co-ordinates in a large matrix (diagonally)

If I explain why, this might make more sense

I have a logical matrix (103x3488) output of a photo of a measuring staff having been run through edge detect (1=edge, 0=noedge). Aim- to calculate the distance in pixels between the graduations on the staff. Problem, staff sags in the middle.

Idea: User inputs co-ordinates (using ginput or something) of each end of staff and the midpoint of the sag, then if the edges between these points can be extracted into arrays I can easily find the locations of the edges.

Any way of extracting an array from a matrix in this manner?

Also open to other ideas, only been using matlab for a month, so most functions are unknown to me.

edit: Link to image

It shows a small area of the matrix, so in this example 1 and 2 are the points I want to sample between, and I'd want to return the points that occur along th开发者_Go百科e red line.

Cheers

Try this

dat=imread('83zlP.png');

figure(1)
pcolor(double(dat))
shading flat
axis equal

% get the line ends
gi=floor(ginput(2))
x=gi(:,1);
y=gi(:,2);

xl=min(x):max(x); % line pixel x coords
yl=floor(interp1(x,y,xl)); % line pixel y coords


pdat=nan(length(xl),1);
for i=1:length(xl)
    pdat(i)=dat(yl(i),xl(i));
end

figure(2)
plot(1:length(xl),pdat)

peaks=find(pdat>40); % threshhold for peak detection
bigpeak=peaks(diff(peaks)>10); % threshold for selecting only edge of peak

hold all
plot(xl(bigpeak),pdat(bigpeak),'x')
meanspacex=mean(diff(xl(bigpeak)));
meanspacey=mean(diff(yl(bigpeak)));
meanspace=sqrt(meanspacex^2+meanspacey^2);

The matrix pdat gives the pixels along the line you have selected. The meanspace is edge spacing in pixel units. The thresholds might need fiddling with, depending on the image.

After seeing the image, I'm not sure where the "sagging" you're referring to is taking place. The image is rotated, but you can fix that using imrotate. The degree to which it needs to be rotated should be easy enough; just input the coordinates A and B and use the inverse tangent to find the angle offset from 0 degrees.

Regarding the points, once it's aligned straight, all you need to do is specify a row in the image matrix (it would be a 1 x 3448 vector) and use find to get non-zero vector indexes. As the rotate function may have interpolated the pixels somewhat, you may get more than one index per "line", but they'll be identifiable as being consecutive numbers, and you can just average them to get an approximate value.