Finding thick objects on binary image

Question

In the context of analysing images to find zones with movement, here's what I've got as an intermediate result, using opencv with python (assume these are 100% binary):

So my question is: is there a way to locate blobs of white with a specific "thickness" threshold ?

Here's what it could look like, roughly:

I've been looking for transforms and manipulations such as connected components and morphological transformations but those won't work and I can't quite figure out where to start other than that.

Cris Luengo · Accepted Answer · 2022-03-31 18:19:08Z

3

The morphological opening is ideal for this problem. It removes all the white parts thinner than a given diameter.

In OpenCV it is implemented in cv2.morphologyEx using op=cv2.MORPH_OPEN:

kernel = cv2.getStructuringElement(cv2.cv.MORPH_ELLIPSE, diameter)
output = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)

But note that this removes parts of objects that are thin, it doesn't leave the full object if a part of it is wide enough. That can be done using an opening by reconstruction, an erosion followed by a morphological reconstruction (also known as geodesic dilation).

OpenCV doesn't have that algorithm. This Q&A gives a rough outline for how to implement it in OpenCV, but that is a very expensive algorithm, there are much more efficient ones.

There might be an implementation in Scikit-image, I haven't looked for it.

DIPlib (with Python bindings called PyDIP) (also, I'm an author) has a dip.OpeningByReconstruction. Install the Python module with pip install diplib.

edited Mar 31, 2022 at 18:19

answered May 16, 2019 at 22:06

Cris Luengo

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2 Comments

RobertMoga Over a year ago

I would also add this webpage containing articles for more extensive explanation regarding morphological operations. After performing an opening you can call cv.boundingRect(img) from openCV to locate the remaining objects.

Cris Luengo Over a year ago

@RobertMoga: Though I appreciate Bob’s work in putting that web site together, the page you link provide a highly incomplete view of Mathematical Morphology. That was the state more or less 50 years ago when the field was created. A lot of things have happened in 50 years.

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