English

Visibility graphs for image processing

Data Analysis, Statistics and Probability 2019-11-19 v1 Machine Learning

Abstract

The family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classification. We demonstrate that the link architecture of the image visibility graphs encapsulates relevant information on the structure of the images and we explore their potential as image filters and compressors. We introduce several graph features, including the novel concept of Visibility Patches, and show through several examples that these features are highly informative, computationally efficient and universally applicable for general pattern recognition and image classification tasks.

Keywords

Cite

@article{arxiv.1804.07125,
  title  = {Visibility graphs for image processing},
  author = {Jacopo Iacovacci and Lucas Lacasa},
  journal= {arXiv preprint arXiv:1804.07125},
  year   = {2019}
}

Comments

16 pages, codes available upon request