GPU accelerated Fourier cross correlation computation and its application in template matching

Abstract

The correlation is an important tool during image processing and pattern recognition, and also widely applied in other image-related fields. The correlation between two images (cross correlation) is deemed as an accurate method to evaluate the similarity of these images. However, a high computational cost to calculate the correlation hinders its wide use. Calculating the correlation by transforming them into Fourier spaces (Fourier cross correlation, FCC) can shorten the computational time to some extent. To further accelerate the computation speed based on the FCC computation, we introduce CUDA GPU and compare the performance of both GPU and CPU. Our comparison results show that there is a 10 times speed up when computing FCC between 4096*4096 pixel images on NVIDIA GeForce 9400. We obtained the similar results when implementing FCC in rotation cases. The accelerated FCC algorithm based on GPU is proved to take effect in a template matching application. © 2011 Springer-Verlag.