Target recognition using cepstrum and inverse filtering
Sharon X. Wang, Carl D. Crane, Murali Rao, Dan Ekdahl, James S. Tulenko · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
This research proposes an algorithm to recognize a target that may differ from a reference template in position, scale, and in-plane rotation. The proposed algorithm accomplishes the recognition in two steps: rotation and scale detection followed by translation detection. In the first step, the Fourier transformation of the cepstrum is used to achieve the translation invariance, and a polar-logarithmic coordinate system is employed to convert the scale and rotation changes into linear shifts. In the second step, the template is regenerated to the correct size and orientation using rotation and scale parameters obtained from step one. In both steps matching is accomplished using template inverse filtering, which generates a Dirac delta function that appears as a sharp peak. The distinguishing features of this system are three-fold. First, while detecting the existence of the target, it provides the translation, scale, and rotation parameters, which are often needed in many applications. Secondly, it employs the template inverse filters to increase the auto-correlation peaks and suppress the cross-correlation coefficients and noise. Thirdly, it utilizes the cepstrum instead of the spectrum to enhance the high frequency components, and therefore improves the recognition significantly for scale and rotation detection. Experimental examples demonstrate recognition results.