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In theory, as chain code is very sensitive to noise we should:

• Superimpose a sampling grid
• Resample to some fixed number of points

I have seen this approach many places but not an implementation anywhere. Or can we implement it using opencv?

For example I have this image, I apply Canny edge detection. Then how do I make it become as follows:

I do not even know how to place grid on the image and obtain the boundary vertices.

In theory, as chain code is very sensitive to noise we should:

• Superimpose a sampling grid
• Resample to some fixed number of points

I have seen this approach many places but not an implementation anywhere. Or can we implement it using opencv?

In theory, as chain code is very sensitive to noise we should:

• Superimpose a sampling grid
• Resample to some fixed number of points

I have seen this approach many places but not an implementation anywhere. Or can we implement it using opencv?

For example I have this image, I apply Canny edge detection. Then how do I make it become as follows:

I do not even know how to place grid on the image and obtain the boundary vertices.

I have tried this:this using the suggestion of Tetagramm:

In theory, as chain code is very sensitive to noise we should:

• Superimpose a sampling grid
• Resample to some fixed number of points

I have seen this approach many places but not an implementation anywhere. Or can we implement it using opencv?

For example I have this image, I apply Canny edge detection. Then how do I make it become as follows:

I do not even know how to place grid on the image and obtain the boundary vertices.

I have tried this using the suggestion of Tetagramm:Tetragramm: