Analysis of sequential complex images, using feature extraction and two-dimensional cepstrum techniques

Abstract

The analysis of a class of complex images has been simplified by extracting the edge-dominated features before matching the sequential images. The consecutive images are then registered by a frequency-domain technique, specifically by a combination of two-dimensional power spectrum and cepstrum techniques to correct for rotational and translational shifts, respectively. The cepstrum technique is found to be more accurate for correction of a translational shift than are the commonly used phase-correlation techniques and spatial-domain-correlation techniques, particularly for noisy and nonuniformly featured sequential images. The change in sequential images is expressed quantitatively in terms of the mean and the variance of the computed two-dimensional histogram representing the difference of two consecutive images. Such quantitative measures of change in sequential images have been applied to a class of complex medical images, namely, retinal (fundus) images, to provide a diagnostic measure for early detection of glaucoma. However, the general procedure of using feature-extraction techniques first and then registering and analyzing images by using power-spectrum and two-dimensional cepstrum techniques provides an unambiguous, accurate, and fast technique for the analysis of a broad range of sequential complex images.