image processing - surfnorm function more efficient way Matlab -


after constructing point cloud want normal of each point , used built-in matlab function surfnorm takes lot of processing time. if assist me better , more efficient way.

i wonder if following code you. there 3 steps here.

  1. create 500 randomly spaced points (x,y), , compute corresponding value z (the height of surface) chose sinc function
  2. resample random points using triscatteredinterp function - permits me obtain points on evenly sampled grid "roughly correspond" initial surface
  3. compute normal "some points" on grid (since there 480x640 points, computing normal @ every point create impossibly dense "forest of vectors"; sampling "every 10th point" can see doing

the code used follows:

randomx = rand(1,500); randomy = rand(1,500); r = 5*sqrt(randomx.^2 + randomy.^2); randomz = sin(r) ./ r;  % resample data: [xx yy] = meshgrid(linspace(0,1,640), linspace(0,1,480)); f = triscatteredinterp(randomx(:), randomy(:), randomz(:)); zz = f(xx, yy);  %% @ each point, normal cross product of vectors neighbors xyz=reshape([xx yy zz],[size(xx) 3]); xv = 10:30:479; yv = 10:30:639; % points @ compute normals dx = xyz(xv, yv+1, :) - xyz(xv, yv, :); dy = xyz(xv+1, yv, :) - xyz(xv, yv, :);  normvecs = cross(dx, dy); % here compute normals. normvecs = normvecs ./ repmat(sqrt(sum(normvecs.^2, 3)), [1 1 3]);  figure; quiver3(xx(xv, yv), yy(xv, yv), zz(xv, yv), ...     normvecs(:,:,1), normvecs(:,:,2), normvecs(:,:,3)); axis equal view([56 22]);

and resulting plot:

enter image description here


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