# A Functional Data Framework For Analyzing Shapes and Textures in Images

Source: [A Functional Data Framework For Analyzing Shapes and Textures in Images](<https://www.sota2.com/research/paper/6a28f38390966ade919c1a8c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-06-24T05:00:13.022Z

Authors: Issam-Ali Moindji\\'e

Published: 2026-06-09T15:11:52.000Z

## Abstract

Images represent objects characterized by contours and textures. From a statistical perspective these features can be defined as observations of continuous random functions. However, most existing approaches rely on pixel-based discretizations which lead to high-dimensional representations and heavy computational costs. In this note, we introduce an alternative more frugal representation. This representation assumes that the object has a star-shaped domain interior. Under this condition, we explore the analysis of images from a functional data analysis perspective. The proposed framework is illustrated on a real data supervised image classification problem.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2606.10969>)

[PDF](<https://arxiv.org/pdf/2606.10969.pdf>)