IMAGE SIMILARITY USING FOURIER TRANSFORM

In this paper, a similarity measure for images base d on values from their respective Fourier Transforms is proposed for image registration. The approach uses image content to generate signatures and is not based on image annotation and therefore does not require human assistance. It uses both, the real and complex components of the F FT to compute the final rank for measuring similarity. Any robust approach must accurately rep resent all objects in an image and depending on the size of the image data set, diverse techniques may need to be followed. This paper discusses implementation of a similarity rating scheme through the Open CV library and introduces a metric for comparison, carried out by considering Intersection bounds of a covariance matrix of two compared images with normalized values of the Magnitude and Phase spectrum.