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I have images that consist of vegetation disponsed in lines (may or may not be straight lines).

I need to implement an algorithm that identifies those lines and produces a binary mask image tagging the vegetation pixels. This mask can whether be a dense mask (flagging all the identified vegetation pixels) or skeleton mask (1-pixel wide lines identifying the center of the vegetation lanes).

Here is an example of input images:

And here is one of the possible expected outputs:

So far, I've tried the following approaches which result in the following problems:

• Canny edge detector: yields lots of false positives due to shadows
• Image threshold: yields false positives due to ground vegetation.

Anyone has more ideas?

Thanks

I have images that consist of vegetation disponsed in lines (may or may not be straight lines).

I need to implement an algorithm that identifies those lines and produces a binary mask image tagging the vegetation pixels. This mask can whether be a dense mask (flagging all the identified vegetation pixels) or skeleton mask (1-pixel wide lines identifying the center of the vegetation lanes).

Here is an example of input images:

And here is one of the possible expected outputs:

So far, I've tried the following approaches which result in the following problems:

• Canny edge detector: yields lots of false positives due to shadows
• Image threshold: yields false positives due to ground vegetation.

Anyone has more ideas?

Thanks