Phase-Correlation Guided Search for Realtime Stereo Vision
IWCIA '09 Proceedings of the 13th International Workshop on Combinatorial Image Analysis
Texture defect detection system with image deflection compensation
WSEAS Transactions on Computers
Parametric Estimation of Affine Transformations: An Exact Linear Solution
Journal of Mathematical Imaging and Vision
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
3-D Symmetry Detection and Analysis Using the Pseudo-polar Fourier Transform
International Journal of Computer Vision
Local affine image matching and synthesis based on structural patterns
IEEE Transactions on Image Processing
Optical flow estimation with prior models obtained from phase correlation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Rigid registration of renal perfusion images using a neurobiology-based visual saliency model
Journal on Image and Video Processing
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
A hybrid swipe fingerprint mosaicing scheme
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Phase correlation based image alignment with subpixel accuracy
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
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One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This work presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms.