Field of view/ convexity map

Question

On a shape from a logical image, I am trying to extract the field of view from any point inside the shape on matlab :

enter image description here

I tried something involving to test each line going through the point but it is really really long.(I hope to do it for each points of the shape or at least each point of it's contour wich is quite a few times)

I think a faster method would be working iteratively by the expansion of a disk from the considered point but I am not sure how to do it.

How can I find this field of view in an efficient way?

Any ideas or solution would be appreciated, thanks.

What do you mean by 'field of view'? Can you elaborate and maybe show an image. Are you looking for the minimal distance to the edge? — Cape Code, Nov 20 '14 at 18:54
I added a picture. I am looking for all the locations accessible by the point with a straight line. (the shape thing was to be more precise but it may be too much here) — Jimolrame, Nov 21 '14 at 10:19
I think I have a code that does just that. Do you have the image processing toolbox? — Cape Code, Nov 21 '14 at 14:37
yes I have the version 8.1. How does the code works? I can give it a try with a few indications. — Jimolrame, Nov 24 '14 at 17:28
Sorry it took me some time, see my answer and the linked function available for download. — Cape Code, Dec 03 '14 at 17:59

score 0 · Accepted Answer · answered Dec 03 '14 at 17:20

Here is a possible approach (the principle behind the function I wrote, available on Matlab Central):

I created this test image and an arbitrary point of view:

testscene=zeros(500);
testscene(80:120,80:120)=1;
testscene(200:250,400:450)=1;
testscene(380:450,200:270)=1;

viewpoint=[250, 300]; 
imsize=size(testscene); % checks the size of the image

It looks like this (the circle marks the view point I chose):

scene

The next line computes the longest distance to the edge of the image from the viewpoint:

maxdist=max([norm(viewpoint), norm(viewpoint-[1 imsize(2)]), norm(viewpoint-[imsize(1) 1]), norm(viewpoint-imsize)]);

angles=1:360; % use smaller increment to increase resolution

Then generate a set of points uniformly distributed around the viewpoint.:

endpoints=bsxfun(@plus, maxdist*[cosd(angles)' sind(angles)'], viewpoint);

for k=1:numel(angles)
        [CX,CY,C] = improfile(testscene,[viewpoint(1), endpoints(k,1)],[viewpoint(2), endpoints(k,2)]);
        idx=find(C);
        intersec(k,:)=[CX(idx(1)), CY(idx(1))];
end

What this does is drawing lines from the view point to each directions specified in the array angles and look for the position of the intersection with an obstacle or the edge of the image.

This should help visualizing the process: intersections

Finally, let's use the built-in roipoly function to create a binary mask from a set of coordinates:

FieldofView = roipoly(testscene,intersec(:,1),intersec(:,2));

Here is how it looks like (obstacles in white, visible field in gray, viewpoint in red):

final scene

np for the time. That's perfect for what I want to do and way faster than what I was doing. — Jimolrame, Dec 04 '14 at 10:43
Note : For the file on Matlab central you may want to use the input image as a mask for the output "visiblefield" to clean the borders of the shapes in the field of view. thanks a lot — Jimolrame, Dec 04 '14 at 10:56

Field of view/ convexity map

1 Answers1