REVIEW OF CORRELATION BASED ALGORITHMS IN SIGNAL AND IMAGE PROCESSING FOR PATTERN IDENTIFICATION

Abstract

This paper presents a review of applications of Digital Correlation algorithms in pattern
identification in signal and image processing. The paper not only describes the correlation function, and its
different variants descriptively and mathematically and the algorithms in which these can perform
discrimination among several signals, images, video frames and objects within them, it also explains the
implementation of these by using synthetic signals, audio signals and images, including alphabetic characters.
Apart from this, the paper also includes the pseudo code for better understanding of algorithms from the
implementation point of view. The results of all described techniques are presented from unprocessed original
signals to their processed from, graphically, and spatially.
As an extended version [11], this paper presents a few more applications of Digital Correlation related
functions for more complex tasks and it has been found that, the Digital Correlation and its related functions are
very useful and easy to implement for real life pattern identification problems with enough level of complexity
with less computational efforts as an independent algorithm and as a part of a complex algorithm.