CS Other Presentations

Department of Computer Science - University of Cyprus

Besides Colloquiums, the Department of Computer Science at the University of Cyprus also holds Other Presentations (Research Seminars, PhD Defenses, Short Term Courses, Demonstrations, etc.). These presentations are given by scientists who aim to present preliminary results of their research work and/or other technical material. Other Presentations serve as a forum for educating Computer Science students and related announcements are disseminated to the Department of Computer Science (i.e., the csall list):
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Presentations Coordinator: Demetris Zeinalipour

PhD Defense: Efficient Image Representations Using Multiscale AM-FM Decompositions Derived from Multiple Gabor Filterbanks, Mr. Ioannis Constantinou (University of Cyprus, Cyprus), Monday, December 11, 2017, 10.00-11.00 EET.


The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:

Efficient Image Representations Using Multiscale AM-FM Decompositions Derived from Multiple Gabor Filterbanks

Speaker: Mr. Ioannis Constantinou
Affiliation: University of Cyprus, Cyprus
Category: PhD Defense
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Monday, December 11, 2017
Time: 10.00-11.00 EET
Host: Chris Christodoulou (cchrist-AT-cs.ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/presentations.php?speaker=cs.ucy.pres.2017.constantinou

Abstract:
Multiscale AM-FM decompositions have provided effective methods for representing non-stationary content in digital images. Furthermore, AM-FM models have long been associated with mathematical models of the human visual system. In a standard application, AM-FM decompositions are derived from the outputs of a Gabor filterbank, after possible pre-filtering by a 2D Hilbert Transformer. Yet, the human visual system is known to use a large number of Gabor filters that significantly outnumber the ones found in a single filterbank. In this dissertation it is documented that the use of multiple Gabor filterbanks can lead into more efficient image representations that perform significantly better compared to the current use of a single Gabor filterbank. To quantify the advantages of using multiple filterbanks, the thesis explores their application in the computation of multiscale AM-FM decompositions and the analysis of real images. For this purpose, we developed three new AM-FM decomposition methodologies: a) a decomposition methodology based on a stepwise scalable-quality increase in the reconstruction quality, b) a multiscale decomposition methodology and c) a directional decomposition methodology. From the results of the application of the above-mentioned methodologies it is evident that the use of multiple families of filterbanks offers significant benefits to the precision of estimating the instantaneous amplitude, instantaneous frequency and reconstruction quality as compared to conventional methodologies and using only one family of filterbanks. We also applied the proposed methodologies in the classification of gynecological endometrial cancer with very good results.

Short Bio:
Mr. Ioannis Constantinou is a PhD candidate in area of image analysis, at Department of Computer Science, University of Cyprus under supervision of professor Constantinos Pattichis. Mr. Constantinou received his diploma degree in Electrical & Computer Engineering from the National Technical University of Athens (NTUA), in 2006 and an MSc in Biomedical Engineering from Interdepartmental Program of the University of Patras and National Technical University of Athens in 2008. Since 2008, he serves as researcher of e-Health lab of the Computer Science Department of the UCY. Mr. Constantinou has been involved in several EU-funded and locally-funded research projects related to telemedicine, image processing and analysis, biological procedure modeling and simulation. He contributed to more than 20 papers in scientific conference and journals in the area of medical image analysis, robotics and computer vision.

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