IMAGE SIMILARITY USING FOURIER TRANSFORM
Siddharth Narayanan, P K Thirivikraman · 2015
In this paper, a similarity measure for images based 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 FFT to compute the final rank for measuring similarity. Any robust approach must accurately represent 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. Sample results on a test collection are given along with data using existing methods of image histogram comparison. Results have shown that this method is particularly advantageous in images with varying degrees of lighting.