Application of a registration method based on SVD in detecting moving object of dynamic background

This paper proposes a method used to detect big moving object in the complicated dynamic background, which integrates the phase correlation technique including singular value decomposition and the method in which multi-frames difference images is multiplied. The phase correlation algorithm based on singular value decomposition is insensitive to noise and change of gray and contrast. Comparing with many complex phase correlation algorithm and registration algorithm in spatial domain, our method not only can effectively restrain noise, but also enhancing the registration precision, whose speed is nearly two times as quickly as original phase correlation algorithm. The fact is found by the result of experiment that the phase correlation matrix is rank one for a noise-free rigid translation model. A new phase correlation matrix is recast based on the property which can effectively restrain noise and change of gray. By estimating global moving vector of two images using phase correlation based on singular value decomposition, background is accurately matched. The matched images are processed to calculate the image differences between the first and fourth, the second and fifth, the third and sixth. After these difference images are multiplied, clear edge of moving object is obtained. Thus the accurate location of object is realized by calculating barycentre of image. At last, simulation results prove that this proposed method can overcome effectiveness well in the lighting variations and noise. It is also efficient and applicable for accurate moving object orientation in the complicated dynamic background.