In this article, I’m going to present a low-degree polynomial runtime image partition algorithm that can quickly and reliably partition an image into objectively distinct regions, using only the original image as input, without any training dataset or other exogenous information. All of the code necessary to run the algorithm is available on my code bin.
There’s also a simple script “Consolidate Partition – CMND LINE” that consolidates these features into larger objects.
I’ll follow up with a “crawler” that will assign contiguous regions unique labels to make feature extraction more convenient.
Article: Vectorized Image Partitioning