MATLAB: How to extract XYZ data from Isosurface

extractisosurfacexyz

I have a 3D array of data. There is a distinct ellipsoid shape in the middle. I would like to extract the coordinate points that describe that ellipsoid. Using the isosurface function, I have found the ellipsoid, and it is correct. Is there a way to extract XYZ coordinate data from the isosurface function? Or, is there a more elegant way to extract 3D coordinate points from a 3D array of data where there is a specific value that comprises the shape?

Best Answer

Why not just use find()?

[rows, columns, slices] = find(array3D == someValue);

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MATLAB: Divide a 3D shape into equal-volume subregions

Based on the comments, my original question was too open ended, so I am answering this to bring it to a close. A simple 3D division of the space inside the volume into cubes is good enough, something like,

load('seamount.mat', 'x', 'y', 'z'); % Generic data that comes with Matlab; contains 3D points
% Make the example shape less flat!
x = x*5000; 
y = y*8000; 
DT = delaunayTriangulation(x,y,z); % 3D triangulization of points
[C, volHull] = convexHull(DT); % Compute convex hull, which is cone-shaped
figure('Name', 'Convex Hull');  
hPatch = trisurf(C,DT.Points(:,1),DT.Points(:,2),DT.Points(:,3), ...
    'FaceAlpha', 0.1);
nCubesDesired = 100; 
cubeLength = range(z)/round(nCubesDesired^(1/3)); 
xGrid = min(x):cubeLength:max(x); 
yGrid = min(y):cubeLength:max(y);
zGrid = min(z):cubeLength:max(z);
% Loop through each cube and check if it is inside the volume using 
% in_polyhedreon from File Exchange
% https://www.mathworks.com/matlabcentral/fileexchange/48041-in_polyhedron
% If it is not inside the volume, throw the cube out.
set(gca, 'xtick', xGrid, 'ytick', yGrid, 'ztick', zGrid);
grid on;
% Iterate on cubeLength until you get the desired number of cubes

MATLAB: Silhouette outline of polygon surface

Here is what I came up with:

%%Sean's try
% Here's the general approach: 
%

% # Calculate the Delaunay Triangulation in three dimensions to create
%   tetrahedra forming the shape.
% # Use the x and y coordinates of this triangulation to build two
%   dimensional polygons irrespective of Z.
% # Calculate the union of all of these two dimensional polygons to get the minimal
%   bounding polygon.
%
% 03/21/2013
%%Original Data
xyz = [5, 2, 6, 0, 3;  0, 2, 4, 2, 1;  5, 6, 6, 7, 9]';
tri = [1, 2, 4; 1, 5, 4; 1, 2, 5; 2, 3, 5; 2, 4, 3; 3, 4, 5] ;
FV = struct('faces',tri,'vertices',xyz);
%%Delaunay Triangulation
tri3  = triangulation(tri,xyz);
%%Engine:
% Disable warning since we don't need anything depending on CW v. CCW
warning('off','map:polygon:noExternalContours');
% Initialize final polygon vectors
px = [];
py = [];
% Unionize each polygon with the group using |polybool()| from Mapping
% Toolbox
for ii = 1:size(tri3.ConnectivityList,1)
    [px, py] = polybool('union',...
        tri3.Points(tri3.ConnectivityList(ii,:),1),...
        tri3.Points(tri3.ConnectivityList(ii,:),2),...
        px,py);        
end
%%Visualize and Compare:
figure;
patch(FV,'FaceColor','c','FaceAlpha',0.95);
line(px,py,zeros(size(px)),'color','r','LineWidth',3)
view(2); % How did we do?
title('Woohoo!');

Best Answer

Related Solutions

MATLAB: Divide a 3D shape into equal-volume subregions

MATLAB: Silhouette outline of polygon surface

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