mlsanityData to 14 Oct 2026

Pseudo-Boolean Polynomials Approach To Edge Detection And Image Segmentation

arXiv 2308.15453 ↗First posted 29 Aug 2023cs.CV cs.DMcited by 0

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Abstract (arXiv)

We introduce a deterministic approach to edge detection and image segmentation by formulating pseudo-Boolean polynomials on image patches. The approach works by applying a binary classification of blob and edge regions in an image based on the degrees of pseudo-Boolean polynomials calculated on patches extracted from the provided image. We test our method on simple images containing primitive shapes of constant and contrasting colour and establish the feasibility before applying it to complex instances like aerial landscape images. The proposed method is based on the exploitation of the reduction, polynomial degree, and equivalence properties of penalty-based pseudo-Boolean polynomials.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 17 references that are in the map. First posted on arXiv 29 Aug 2023.

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References · 5

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2017Mask R-CNNcited by 7,277
  3. 2018Panoptic Segmentationcited by 802
  4. 2020Learning Panoptic Segmentation from Instance Contourscited by 4
  5. 2013Performing edge detection by difference of Gaussians using q-Gaussian kernelscited by 3

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