Research - Faculty
Professor and Chairman Kenneth Barner
Research Interests
Prof. Barner's research interests focus on signal and image processing as well as human-computer interaction. The processing of signals is fundamental to applications in a broad array of disciplines, from biology and medicine, to communications and imaging. Traditional signal processing methods employ linear techniques. Real-world systems and signals, however, often exhibit nonlinearities. Moreover, linear methods break down in the presence of harsh environments, such as those characterized by impulsive, or heavy tailed distributions. Thus current work focuses on developing, analyzing, and employing nonlinear signal processing methods that are robust to harsh environments and able to exploit system nonlinearities. Such methods are actively being used to address biomedical applications, including EEG and ECG processing, medical imaging applications such as tomographic and tomosynthesis reconstruction, and detection/estimation in sensor networks. Signal and image processing methods also play a critical role in human-computer interaction systems. For instance, properly designed image processing techniques can transform images to representations that are better comprehended by individuals with color vision deficiencies. Similarly, information bearing structures in visual images can be extracted through signal processing techniques and represented as tactile features to enable access by blind individuals. Current research focuses on optimal algorithms for these applications as well as the development of image-based gesture recognition techniques and deformable volume-object representations for surgery simulation.
