Image correlation by one-dimensional signatures invariant to rotation, position, and scale using the radial Hilbert transform optimized

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.