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Bob DonyBASc (Waterloo), MASc (Waterloo), PhD (McMaster),PEng, CEng, FIET, FEC Associate Professor School of Engineering University of Guelph Guelph, Ontario, Canada N1G 2W1 Voice: +1 519 824-4120 x53458 Fax: +1 519 836-0227 Email: rdony@uoguelph.ca |
Research
Much of my research interests focus on the use of neural network and other adaptive techniques for image and signal processing. A novel neural network, the mixture of principal components (MPC), has been successfully used in image compression within a block transform framework. Because of its locally adaptive nature, it can out-perform the globally optimal Karhunen-Loeve transform (KLT). The network has also been applied to colour image segmentation and in a neuro-fractal image compression scheme. Other work in this vein has seen the development of a nonlinear, neural network based wavelet coding method.
Another focus of my work has been medical imaging. Some of the applications for the above compression methods has been on medical images. Other work includes multimodal image registration, and the analysis of equine tendon sonograms.
Extending the neural approaches from images to audio signals has yielded some promising results. We have been using neural network architectures and other nonlinear, adaptive techniques for speech enhancement and noise reduction. Of particular interest is the application of such advanced DSP techniques to digital hearing aids.
A final interest of mine is in image mosaicing and 3D reconstruction from moving monocular video. This interest stems from work I did for the National Geographic Magazine in 2000, the result of which was the publishing of a mosaic of the USS Arizona shipwreck sunk at Pearl Harbor in the June, 2001 issue. My current work in this regard is the extraction of a three-dimensional relief from unconstrained moving monocular video.
Academics
I've been teaching in the School of Engineering at the University of Guelph since 1997 (and for two year previously at Wilfrid Laurier University). I was hired on for the relatively new Engineering Systems & Computing (ES&C) program. But, because the engineering faculty is not departmentalized, I also feel at home in the Biological Engineering group.
Since being at Guelph, I've taught a number of courses including ENGG*2400 Engineering Systems Analysis, ENGG*3100 Engineering and Design III, ENGG*3390 Signal Processing. I'm looking forward to the first offering of ENGG*4660 Medical Image Processing tentatively scheduled for Winter 2006. I also regularly advise ENGG*41X0 projects that have ranged from 3D vision to the processing of brain waves for a biofeedback game. The group members tend to be a good split between the ES&C and Biological programs.
At the graduate level, I teach ENGG*6560 Advanced Digital Signal Processing, and ENGG*6070 Medical Imaging.