Detection of 3D blobs with flat surfaces

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Roohollah Milimonfared 2019-8-25

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回答： darova 2019-8-26

I have a 3D gray-scale array that represents a bag with several objects inside. I need to find (segment) any object with flat surface/s in the bag. Knowing the approximate intensity range of these objects, I binarized the volume, and removed objects with volumes below a threshold.

The result was getting some of those objects as individual blobs and some attached to nearby objects.

Now, I would like to detect blobs with flat surfaces. Any suggestion?

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darova 2019-8-25

What do you mean by 'flat blob'?

Roohollah Milimonfared 2019-8-26

编辑：Roohollah Milimonfared 2019-8-26

That's right. Only expand it to 3D. An example of a 3D blob with flat surfaces is a cylinder (flat surfaces at its two ends).

In my problem, the blobs have more complicated shapes, but some have flat surfaces that I would like to use as a characteristic to detect them.

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Answer 1

Image Analyst 2019-8-26

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编辑：Image Analyst 2019-8-26

Try convhulln() and extract any blob that has points on the convex hull.

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Roohollah Milimonfared 2019-8-26

编辑：Roohollah Milimonfared 2019-8-26

在 MATLAB Online 中打开

stats = regionprops3(blob,'ConvexImage','ConvexHull','VoxelList');

The binary blob (right) and its ConvexImage (left):

C = intersect(stats.ConvexHull{1,1},stats.VoxelList{1,1},'rows');

C is empty which means the blob has no point on its convex hull.

Below is the plot of voxels (red) and convex hull points (blue). On the top surface, the convex hull points are located at the edges. Can we use this fact to say it is a (nearly) flat surface?

Roohollah Milimonfared 2019-8-26

编辑：Roohollah Milimonfared 2019-8-26

在 MATLAB Online 中打开

I have come up with this trivial solution.

In this problem, the direction of the flat surface is fixed (y-axis is always the axis normal to the flat surface). Sort the y-coordinates (the first column in ConvexHull) in descending order:

ConvexHull = stats.ConvexHull{1,1};
ConvexHull = sortrows(ConvexHull,1,'descend');

Find the Standard Deviation of the first 10% of the ConvexHull coordinates.

threshold = size(ConvexHull,1) * 0.1;
y_coor = ConvexHull(1:threshold,1);
x_coor = ConvexHull(1:threshold,2);
z_coor = ConvexHull(1:threshold,3);
y_std = std(y_coor) % 0.948
x_std = std(x_coor) % 23.676
z_std = std(z_coor) % 49.474