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Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement
The Mexican Hat wavelet (MHW) is strictly derived from the heat kernel by taking its negative first-order derivative with respect to time t. As a solution to the heat equation that the heat kernel has a clear initial condition, the Laplace–Beltrami operator. Although the MHW descriptor can effective...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925734/ https://www.ncbi.nlm.nih.gov/pubmed/36782005 http://dx.doi.org/10.1038/s41598-023-29047-4 |
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author | Yan, Yuhuan Zhou, Mingquan Zhang, Dan Geng, Shengling |
author_facet | Yan, Yuhuan Zhou, Mingquan Zhang, Dan Geng, Shengling |
author_sort | Yan, Yuhuan |
collection | PubMed |
description | The Mexican Hat wavelet (MHW) is strictly derived from the heat kernel by taking its negative first-order derivative with respect to time t. As a solution to the heat equation that the heat kernel has a clear initial condition, the Laplace–Beltrami operator. Although the MHW descriptor can effectively characterize the model information, but it has poor robustness to the model with scale transformation, and the feature description performance is affected to some extent. Following a popular mathematical method, in this paper, we bases on the MHW to study scaling invariance and proposes a new shape descriptor, the scale-invariant Mexican Hat wavelet (SIMHW), which by logarithmic sampling and Fourier transform that obtains the expression of SIMHW in Fourier domain. The experimental results show that SIMHW has finer information description ability and stronger recognition ability, and has better robustness to various non-rigid transformations. It can correctly calculate the similarity between 3D shapes and realize the effective shape retrieval. |
format | Online Article Text |
id | pubmed-9925734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99257342023-02-15 Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement Yan, Yuhuan Zhou, Mingquan Zhang, Dan Geng, Shengling Sci Rep Article The Mexican Hat wavelet (MHW) is strictly derived from the heat kernel by taking its negative first-order derivative with respect to time t. As a solution to the heat equation that the heat kernel has a clear initial condition, the Laplace–Beltrami operator. Although the MHW descriptor can effectively characterize the model information, but it has poor robustness to the model with scale transformation, and the feature description performance is affected to some extent. Following a popular mathematical method, in this paper, we bases on the MHW to study scaling invariance and proposes a new shape descriptor, the scale-invariant Mexican Hat wavelet (SIMHW), which by logarithmic sampling and Fourier transform that obtains the expression of SIMHW in Fourier domain. The experimental results show that SIMHW has finer information description ability and stronger recognition ability, and has better robustness to various non-rigid transformations. It can correctly calculate the similarity between 3D shapes and realize the effective shape retrieval. Nature Publishing Group UK 2023-02-13 /pmc/articles/PMC9925734/ /pubmed/36782005 http://dx.doi.org/10.1038/s41598-023-29047-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yan, Yuhuan Zhou, Mingquan Zhang, Dan Geng, Shengling Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title | Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title_full | Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title_fullStr | Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title_full_unstemmed | Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title_short | Scale-invariant Mexican Hat wavelet descriptor for non-rigid shape similarity measurement |
title_sort | scale-invariant mexican hat wavelet descriptor for non-rigid shape similarity measurement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925734/ https://www.ncbi.nlm.nih.gov/pubmed/36782005 http://dx.doi.org/10.1038/s41598-023-29047-4 |
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