Harmonic Beltrami Signature: A Novel 2D Shape Representation for Object Classification
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Abstract (arXiv)
There is a growing interest in shape analysis in recent years. We present a novel shape signature for 2D bounded simply-connected domains, named the Harmonic Beltrami signature (HBS). The proposed signature is based on the harmonic extension of the conformal welding map of a unit circle and its Beltrami coefficient. We show that there is a one-to-one correspondence between the quotient space of HBS and the space of 2D simply-connected shapes up to a translation, rotation and scaling. With a suitable normalization, each equivalence class in the quotient space of HBS is associated to a unique representative. It gets rid of the conformal ambiguity. As such, each shape is associated to a unique HBS. Conversely, the associated shape of a HBS can be reconstructed based on quasiconformal Teichmuller theories, which is uniquely determined up to a translation, rotation and scaling. The HBS is thus an effective fingerprint to represent a 2D shape. The robustness of HBS is studied both theoretically and experimentally. With the HBS, simple metric, such as L2, can be used to measure geometric dissimilarity between shapes. Experiments have been carried out to classify shapes in different classes using HBS. Results show good classification performance, which demonstrate the efficacy of our proposed shape signature.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 2 of its 28 references that are in the map. First posted on arXiv 30 Mar 2021.
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2 of 28 references.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 0; 2026: 1.
4 papers.
- 2022A Learning-based Framework for Topology-Preserving Segmentation using Quasiconformal Mappingscited by 10
- 2022Topology-Preserving Segmentation Network: A Deep Learning Segmentation Framework for Connected Componentcited by 4
- 2024Shape Prior Segmentation Guided by Harmonic Beltrami Signaturecited by 1
- 2026Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Frameworkcited by 0
- 2026Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Framework3 Mar 2026
- 2024Shape Prior Segmentation Guided by Harmonic Beltrami Signature5 Jul 2024
- 2022A Learning-based Framework for Topology-Preserving Segmentation using Quasiconformal Mappings7 Oct 2022
- 2022Topology-Preserving Segmentation Network: A Deep Learning Segmentation Framework for Connected Component27 Feb 2022