PROF. DR. RAVEENDRAN A/L PARAMESRAN
Department of Electrical Engineering
Faculty of Engineering
ravee@um.edu.myView CV | |
Biography | |
P. Raveendran received the B.Sc and M.Sc degrees in electrical engineering from South Dakota State University, Brookings, South Dakota, USA in 1984 and 1985 respectively. He was a systems designer with Daktronics, U.S.A before joining the Department of Electrical Engineering at University of Malaya, Kuala Lumpur, as a lecturer in 1986. In 1992, he received a Ronpaku scholarship from Japan to pursue Doctorate in Engineering, which he completed in 1994 at University of Tokushima, Japan. He was promoted to Associate Professor in 1995 and was promoted to Professor in 2003. His research areas include image and video analysis, formulation of new image descriptors for image analysis, fast computation of orthogonal moments, analysis of EEG signals, and data modeling of substance concentration acquired from non-invasive methods. His contributions can be seen in the form of journal publications, conference proceedings, chapters in books and an international patent to predict blood glucose levels using non-parametric model. He has successfully supervised to completion 17 Ph.D students and 13 students in M.Eng.Sc (Masters by research). He is currently a Senior IEEE member and also a member of the Signal Processing Society. |
Publication
Finance
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A method using uniform yellowing pigmentation to model the color perception of the elderly people
Image Denoising using Combined Higher Order Nonconvex Total Variation with Overlapping Group Sparsity
Video Based Heart Rate Estimation Using Facial Images from Video Sequences
Learning based restoration of Gaussian blurred images using Weighted Geometric moments and Cascaded digital filters.
A method using uniform yellowing pigmentation to model the color perception of the elderly people
Image Denoising using Combined Higher Order Nonconvex Total Variation with Overlapping Group Sparsity
Learning based restoration of Gaussian blurred images using Weighted Geometric moments and Cascaded digital filters.
Impulse Noise Detection Technique based on Fuzzy Set
Microprocessors: MC6800 Fundamentals & MC6809 System Design
Mikropemproses Lanjutan 8 bit: MC6809, Perisisan, Perkakasan, Seni-Bina and Antara-Muka
Advanced 8-bit Microprocessor: MC6809, its Software, Hardware, Architecture and Interfacing Techniques