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Plenary Lecture

Digital Image Registration by Swarm Intelligence Algorithms

Professor Milan Tuba
State University of Novi Pazar
Department of Mathematical Sciences
Serbia
E-mail: tuba@ieee.org

Abstract: Digital mage registration represents a problem of great importance in various field such as medicine, security, astronomy, etc. It refers to the problem of matching two or more pictures of the same scene taken at different times, by different sensors, different viewpoints. It is necessary to find a spatial relationship between these images, usually called reference image and floating images. This relationship can be a linear transformation, also known as rigid transformation, or non-linear (nonrigid, elastic) transformation. Image registration techniques can be feature based or area based. Feature based techniques provide transformation which maps floating images to the reference image based on some common features between them. These techniques are limited due the need to find the reliable feature correspondence between images. Area based techniques work with pixel values and search for the optimal parameters for transformation that aligns floating images to the reference image. In order to determine registration quality, some similarity measurement should be defined. Some of the most common similarity measurements are squared intensity differences, cross correlation, mutual information, etc. The main task in image registration is to optimize the similarity metrics, which is a hard optimization problem. In the last two decades nature inspired algorithms, especially swarm intelligence algorithms, have been widely used for solving hard optimization problems. A number of swarm intelligence metaheuristics have been developed and they have been adjusted and tuned for image registration problem. This plenary lecture will present some successful applications of swarm intelligence algorithms to the image registration problem.

Brief Biography of the Speaker: Milan Tuba is the Head of the Department for Mathematical Sciences at State University of Novi Pazar. He received B. S. in Mathematics, M. S. in Mathematics, M. S. in Computer Science, M. Ph. in Computer Science, Ph. D. in Computer Science from University of Belgrade and New York University. From 1983 to 1994 he was in the U.S.A. first as a graduate student and teaching and research assistant at Vanderbilt University in Nashville and Courant Institute of Mathematical Sciences, New York University and later as Assistant Professor of Electrical Engineering at Cooper Union School of Engineering, New York. During that time he was the founder and director of Microprocessor Lab and VLSI Lab, leader of scientific projects and theses supervisor. From 1994 he was Assistant Professor of Computer Science and Director of Computer Center at University of Belgrade, from 2001 Associate Professor, Faculty of Mathematics, University of Belgrade, from 2004 also a Professor of Computer Science and Dean of the College of Computer Science, Megatrend University Belgrade and from 2014 Dean of the Graduate School of Computer Science at John Naisbitt University. He was teaching more than 20 graduate and undergraduate courses, from VLSI Design and Computer Architecture to Computer Networks, Operating Systems, Image Processing, Calculus and Queuing Theory. His research interest includes heuristic optimizations applied to computer networks, image processing and combinatorial problems. Prof. Tuba is the author or coauthor of more than 150 scientific papers and coeditor or member of the editorial board or scientific committee of number of scientific journals and conferences. Member of the ACM, IEEE, AMS, SIAM, IFNA.

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