Image correlation by one-dimensional signatures invariant to rotation, position, and scale using the radial Hilbert transform optimized
| Autor: | Alfredo Castro-Valdez, Selene Solorza-Calderón, Josué Álvarez-Borrego |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Digital image correlation
business.industry Mathematical analysis Nonlinear correlation 01 natural sciences Atomic and Molecular Physics and Optics 010309 optics Correlation symbols.namesake Optics Fourier transform 0103 physical sciences symbols Hilbert transform Electrical and Electronic Engineering Invariant (mathematics) business Engineering (miscellaneous) Mathematics |
| Zdroj: | Applied optics. 59(13) |
| ISSN: | 1539-4522 |
| Popis: | This paper presents a new methodology for pattern recognition invariant to rotation, position, and scale. The method uses the correlation of signatures, where the signatures were created with a new equation called the radial Hilbert transform optimized (RHTO) for longer signatures. An analysis with eight non-homogeneous illumination patterns was performed with 2000 letter variants and 30 phytoplankton species. The higher confidence level was founded using the radial Hilbert optimized methodology. Also, it utilized a correlation called adaptive linear–nonlinear correlation, which gave a better discrimination performance than the nonlinear correlation function. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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