2-d signature of images and texture classification
Computer Vision and Pattern Recognition
2023-01-11 v1 Machine Learning
Abstract
We introduce a proper notion of 2-dimensional signature for images. This object is inspired by the so-called rough paths theory, and it captures many essential features of a 2-dimensional object such as an image. It thus serves as a low-dimensional feature for pattern classification. Here we implement a simple procedure for texture classification. In this context, we show that a low dimensional set of features based on signatures produces an excellent accuracy.
Keywords
Cite
@article{arxiv.2205.11236,
title = {2-d signature of images and texture classification},
author = {Sheng Zhang and Guang Lin and Samy Tindel},
journal= {arXiv preprint arXiv:2205.11236},
year = {2023}
}