Plenary Lecture

Image Segmentation Using Local Binary Patterns

Professor Milan Tuba
John Naisbitt University
Graduate School of Computer Science

Abstract: Digital images and digital image processing facilitated huge advancements in many areas including medical diagnostics, astronomy, ecology, quality control, security, etc. Important step in image analysis is often image segmentation. Based on some criteria, it partitions an image into regions that can be used for understanding of the contents and further analysis. Desired segmentation regions are application dependent. Sometimes they are rather obvious, like in segmenting boat from the sea, and in some cases they are more subtle, like in segmenting abnormal tissue in magnetic resonance images. Accordingly, segmentation criteria can be as simple as intensity level thresholding or more complicated like region entropy or texture differentiating. Local binary patterns are powerful discriminatory features for textures in images while uniform local binary patterns represent a simpler and rotation invariant version. From the local binary patterns histogram many features for texture characterization can be extracted including average value, variance, skewness, kurtosis, energy, entropy, etc. In this plenary lecture some successful applications of local binary patterns and features extracted from their histogram to segmentation of different types of images will be presented.

Brief Biography of the Speaker: Milan Tuba is the Dean of Graduate School of Computer Science and Provost for mathematical and technical sciences at John Naisbitt University of Belgrade. 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, and from 2004 also a Professor of Computer Science and Dean of the College of Computer Science, Megatrend University Belgrade. 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 mathematical, queuing theory and 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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