On identification of human eye retinas by the covariance analysis of their digital images

Abstract

An identification of human eye retinas by applying the covariance function and wavelet theory is presented. The estimations of the autocovariance functions of the two digital images or single image are calculated according to random functions, based on the vectors created from the digital image pixels. The estimations of the pixels vectors are calculated by spreading the pixel arrays of the digital images into single column. During the changing of the scale of the digital image, the wave frequencies of the colors of the single pixels are prekept, and the influence of the change of a scale in the procedures of the calculations of the covariance functions does not occur. The Red, Green, Blue (RGB) color model of the colors spectrum for the encoding of the digital images was applied. The influence of the RGB spectrum components and the tensor of colors on the estimations of the covariance functions were analyzed. The identity of the digital images is estimated by analysis of the changes of the correlation coefficient values in the corresponding diapason. © The Authors.