Blurred image recognition based on phase invariants
A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.
phase invariants fourier transform phase correlation template matching