Image Similarity Estimation Based on Ratio and Distance Calculation between Features

Abstract

Some similarity functions for comparing the features of objects in the processing of static images and video sequences are proposed. These functions provide the possibility to find the normalized similarity value and are determined by calculating the ratios between the minimum and maximum values for all the pairs of analyzed features. To find the complex value characterizing the similarity of compared images as a whole, the summation or multiplication of calculated ratios is used. It is proposed to take into account the distances between features for such types of calculations. Some results of experimental studies on the comparison of the qualitative characteristics of similarity functions, their robustness against different types and levels of noises, and the possibility of the precise localization of objects on an image for the case when the brightness levels of pixels are used as features are presented.

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Correspondence to R. P. Bohush or S. V. Ablameyko or E. R. Adamovskiy or D. Savca.

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Rykhard Bohush graduated from the Polotsk State University in 1997. He received a PhD in the field of information processing at the Institute of Engineering Cybernetics of the National Academy of Sciences of Belarus in 2002. He is head of the Department of Computer Systems and Networks of the Polotsk State University. His scientific interests include image and video processing, object representation and recognition, intelligent systems, and digital steganography.

Sergey Ablameyko was born in 1956 and received a DipMath in 1978, PhD in 1984, DSc in 1990, and Professor in 1992. He is a professor at the Belarusian State University, member of the Editorial Board of Pattern Recognition Letters, Pattern Recognition and Image Analysis and many other international and national journals; Senior Member of IEEE; Fellow of IAPR; Fellow of the Belarusian Engineering Academy; Academician of the National Academy of Sciences of Belarus; Academician of the European Academy; and more. He was the First Vice-President of the International Association for Pattern Recognition IAPR (2006–2008), and President of the Belarusian Association for Image Analysis and Recognition. His scientific interests are image analysis, pattern recognition, digital geometry, knowledge-based systems, geographical information systems, and medical imaging.

Egor Adamovskiy graduated from the Polotsk State University in 2017. He received a degree of Master of Engineering Sciences in the field of information security in 2019, and was a postgraduate student and engineer at the Computer Systems and Networks Department of the Polotsk State University. His research interests include image processing, information security systems, and technical channels for information leakage.

Daniel Savca was born in 1996. He is a magistrate student of the Gas and Petroleum University of Ploiesti, Romania, with a Bachelor’s degree in the field of automation and applied informatics. His scientific interests include self-control systems, image processing, and advanced automation.

Translated by E. Glushachenkova

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Bohush, R.P., Ablameyko, S.V., Adamovskiy, E.R. et al. Image Similarity Estimation Based on Ratio and Distance Calculation between Features. Pattern Recognit. Image Anal. 30, 147–159 (2020). https://doi.org/10.1134/S1054661820020030

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Keywords:

  • comparison and discovery of images
  • similarity functions
  • localization of objects on images and video sequences