Prof. Ing. Reuben A Farrugia

Prof. Ing. Reuben A Farrugia

Prof. Ing. Reuben A Farrugia

  B.Eng.(Hons),Ph.D.,MIEEE

Associate Professor

Room 15B
Faculty of ICT
University of Malta
Msida
  +356 2340 3088
Prof. Reuben Farrugia is an Associate Professor at the University of Malta and has been working in the fields of image processing and computer vision since 2004, He holds a PhD degree from the University of Malta in image/video compression and has been involved in technical and organizational committees of several national and international conferences. In particular, he served as a General Chair on the IEEE International Workshop on Biometrics and Forensics (IWBF) in 2014 and as Technical Programme Co-Chair on the IEEE Visual Communications and Image Processing (VCIP) the same year. He has also been contributing as a reviewer of several journals and conferences including IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Multimedia. He is currently area editor of the Elsevier Journal on Signal Processing: Image Communications. In September 2013 he was appointed as National Contact Point on the European Association of Biometrics (EAB) and elevated to IEEE Senior Membership in September 2017. He has also been involved in three COST Actions (IC1106, IC1206 and IC1003). During the academic year 2015/16 he spent a one-year sabbatical at INRIA Rennes Bretagne Atlantique (France) working on face super-resolution and light field image processing. Prof. Farrugia has secured funding and managed several research projects including the restoration of facial images from CCTV quality videos (Deep-FIR), the development of a low-cost light-field camera system (VoLARe), the estimation of evapotranspiration in agricultural fields from remote sensing (WARM-EO) and the automated generation of facial images from text descriptions (Face:LIFT).
  • Computer Vision
  • Image Processing
  • Biometrics and digital forensics

FARRUGIA, R. and GUILLEMOT, C., 2020. Light Field Super-Resolution using a Low-Rank Prior and Deep Convolutional Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(5), pp. 1162-1175.

FERNANDEZ, F., FARRUGIA, R.A., BIGUN, J., FIERREZ, J. and GONZALES-SOSA, E., 2019. A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning. IEEE Access, 7, pp. 6519.

GALEA, C. and FARRUGIA, R.A., 2018. Matching Software-Generated Sketches to Face Photographs With a Very Deep CNN, Morphed Faces, and Transfer Learning. IEEE Transactions on Information Forensics and Security, 13(6), pp. 1421.

ALONSO-FERNANDEZ, F., FARRUGIA, R.A. and BIGUN JOSEF, 2017. Iris Super-Resolution Using Iterative Neighbor Embedding, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2017, IEEE, pp. 655.

FARRUGIA, R., GALEA, C. and GUILLEMOT, C., 2017. Super Resolution of Light Field Images Using Linear Subspace Projection of Patch-Volumes. IEEE Journal of Selected Topics in Signal Processing, 11(7), pp. 1058.

FARRUGIA, R. and GUILLEMOT, C., 2017. Face Hallucination Using Linear Models of Coupled Sparse Support. IEEE Transactions on Image Processing, 26(9), pp. 19 June.

GALEA, C. and FARRUGIA, R.A., 2017. Forensic Face Photo-Sketch Recognition Using a Deep Learning-Based Architecture. IEEE Signal Processing Letters, 24(11), pp. 1586.

JIANG, X., LE PENDU, M., FARRUGIA, R.A. and GUILLEMOT, C., 2017. Light Field Compression With Homography-Based Low-Rank Approximation. IEEE Journal of Selected Topics in Signal Processing, 11(7), pp. 1132.

FARRUGIA, R. and GUILLEMOT, C., 2016. Model and Dictionary guided Face Inpainting in the Wild, Asian Conference on Computer Vision 2016.

FARRUGIA, R. and GUILLEMOT, C., 2016. Robust face hallucination using quantization-adaptive dictionaries,  Image Processing (ICIP), 2016 IEEE International Conference on, 25-28 Sept. 2016 2016, IEEE, pp. 2381.

FERNANDEZ, F., FARRUGIA, R.A. and BIGUN, J., 2016. Very low-resolution iris recognition via Eigen-patch super-resolution and matcher fusion,  Biometrics Theory, Applications and Systems (BTAS), 2016 IEEE 8th International Conference on, 6-9 Sept 2016, IEEE.

MICALLEF, B.W., DEBONO, C.J. and FARRUGIA, R.A., 2014. Reducing 3D video coding complexity through more efficient disparity estimation. Consumer Electronics, IEEE Transactions on, 60(1), pp. 74-82.

MICALLEF, J.J., FARRUGIA, R.A. and DEBONO, C.J., 2014. Correlation Noise-Based Unequal Error Protected Rate-Adaptive Codes for Distributed Video Coding. Circuits and Systems for Video Technology, IEEE Transactions on, 24(1), pp. 127-140.

FARRUGIA, R.A. and DEBONO, C.J., 2010. A Hybrid Error Control and Artifact Detection Mechanism for Robust Decoding of H.264/AVC Video Sequences. Circuits and Systems for Video Technology, IEEE Transactions on, 20(5), pp. 756-762.

REUBEN A. FARRUGIA and CARL J. DEBONO, 2009. A Support Vector Machine Approach for Detection and Localization of Transmission Errors within Standard H.263++ Decoders IEEE Transactions on Multimedia, 11(7), pp. 1323-1330.

REUBEN A. FARRUGIA and CARL J. DEBONO, 2008. A Robust Error Detection Mechanism for H.264/AVC Coded Video Sequences Based on Support Vector Machines. IEEE Transactions on Circuits and Systems for Video Technologies, 18(12), pp. 1766-1770.

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