2-d signature of images and texture classification
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 31 references that are in the map. First posted on arXiv 10 May 2022.
Builds on
5 of 31 references.
References · 5
- 2016Kernels for sequentially ordered datacited by 84
- 2014Rigid-Motion Scattering for Texture Classificationcited by 52
- 2013Sparse arrays of signatures for online character recognitioncited by 18
- 2018Persistence paths and signature features in topological data analysiscited by 17
- 2021Feature Engineering with Regularity Structurescited by 7
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.