Writing Reusable Digital Geometry Algorithms in a Generic Image Processing Framework

TL;DR

This paper presents a generic image processing framework based on digital geometry algorithms that emphasizes reusability and flexibility through generic programming, facilitating cross-domain experimentation and reducing implementation costs.

Contribution

It introduces a framework that allows writing reusable digital geometry algorithms in a single codebase adaptable to various input types using generic programming.

Findings

Enables code reuse across different digital geometry algorithms

Reduces development effort for new image processing methods

Facilitates cross-domain experimentation in digital geometry

Abstract

Digital Geometry software should reflect the generality of the underlying mathe- matics: mapping the latter to the former requires genericity. By designing generic solutions, one can effectively reuse digital geometry data structures and algorithms. We propose an image processing framework focused on the Generic Programming paradigm in which an algorithm on the paper can be turned into a single code, written once and usable with various input types. This approach enables users to design and implement new methods at a lower cost, try cross-domain experiments and help generalize results