Pattern Recognition and Image Analysis
Invariant representation of orientation fields for fingerprint indexing
Pattern Recognition
Geometrically invariant image watermarking using Polar Harmonic Transforms
Information Sciences: an International Journal
Error analysis and accurate calculation of rotational moments
Pattern Recognition Letters
A novel gray image representation using overlapping rectangular NAM and extended shading approach
Journal of Visual Communication and Image Representation
Computation of level lines of 4-/8-connectedness
Journal of Visual Communication and Image Representation
Hi-index | 0.14 |
This paper introduces a set of 2D transforms, based on a set of orthogonal projection bases, to generate a set of features which are invariant to rotation. We call these transforms Polar Harmonic Transforms (PHTs). Unlike the well-known Zernike and pseudo-Zernike moments, the kernel computation of PHTs is extremely simple and has no numerical stability issue whatsoever. This implies that PHTs encompass the orthogonality and invariance advantages of Zernike and pseudo-Zernike moments, but are free from their inherent limitations. This also means that PHTs are well suited for application where maximal discriminant information is needed. Furthermore, PHTs make available a large set of features for further feature selection in the process of seeking for the best discriminative or representative features for a particular application.