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Representation and comparison methods for semantically different images

  • Representation, Processing, Analysis and Understanding of Images
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Abstract

This paper discusses the methods of presentation and comparison of semantically unrelated images with an assessment of their similarity in original feature space, and in the Space of Canonical Variables (SCV). The projection of source images in SCV is implemented using a two-dimensional canonical correlation analysis algorithm (2D CCA/2D KLT).

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Authors and Affiliations

  1. Saint Petersburg Electrotechnical University, ul. Prof. Popova 5, St. Petersburg, 197376, Russia

    G. A. Kukharev, N. L. Shchegoleva & E. I. Kamenskaya

  2. Westpomeranian University of Technology, Zolnierska, 49, WI ZUT, Szczecin, Poland

    G. A. Kukharev

Authors
  1. G. A. Kukharev
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  2. N. L. Shchegoleva
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  3. E. I. Kamenskaya
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Corresponding author

Correspondence to G. A. Kukharev.

Additional information

The article was translated by the authors.

This paper uses the materials of the report submitted at the 11th International Conference “Pattern Recognition and Image Analysis: New Information Technologies,” Samara, The Russian Federation, September, 23–28, 2013.

Georgii Aleksandrovich Kukharev. Born in Leningrad, Russia. Received PhD (1978) from the Fine Mechanics and Optics Institute (Leningrad, Russia) and degree of doctor of technical science (1986) from the Institute of Automatics and Computer Facilities (ABT, Riga, Latvia). Since 2006, full professor at Szczecin University of Technology, Faculty of Computer Science and Information Systems (Poland), and at Saint Petersburg State Electrotechnical University LETI, Department of Computer Software Environment. In 2001–2003 visiting professor at Ecole Centrale de Lyon, Department of Mathematics and Computer Science. Since 2005 visiting professor at Hanoi University of Technology, Department of International Training Programmer. Author of ten monographs, over 100 scientific papers, and over 40 patents in the areas of computer architecture of signal processing, image processing, and pattern recognition. Current interests are biometrics, including face detection and face recognition, Visitor Identification and access control systems, task Name It, and Face Retrieval.

Nadezhda L’vovna Shchegoleva was born in Komsomolsk-on-Amur, Russia. Received PhD (2000) from St. Petersburg Electrotechnical University (LETI). 2001–2006 she was Senior Researcher at the Okeanpribor Concern Open Joint-Stock Company. Since 2007 she has been Associate Professor at the Computer Software Department in Saint Petersburg Electrotechnical University “LETI”. Coauthor of two monographs, a patent, and more than 50 scientific articles. Current interests are biometric identification systems and access control systems, face detection and face recognition, and synthesis and modeling of recognition systems.

Ekaterina Ivanovna Kamenskaya was born in St. Petersburg, Russia in 1983. She received a degree in Engineering (Computer Science), a BS in Management (2006), and her PhD (2011) from St. Petersburg State Electrotechnical University, Russia. From July 2008 she has worked as a Software Engineer at Google. Her research interests are related to image processing, face recognition, and psychological profiling. She is the coauthor of a monograph and over 15 papers.

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Kukharev, G.A., Shchegoleva, N.L. & Kamenskaya, E.I. Representation and comparison methods for semantically different images. Pattern Recognit. Image Anal. 24, 518–529 (2014). https://doi.org/10.1134/S1054661814040105

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  • DOI: https://doi.org/10.1134/S1054661814040105

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