Image Processing

Narendra Ahuja

Professor Ahuja's work centers on vision and robotics. Improved vision and image processing systems can greatly enhance the options in designing trustworthy and secure systems. One project involves new technical appraoches for face and expression recognition. Accurate face and expression recognition can enhance surveillance and forensic systems.

Yoram Bresler

Prof. Bresler's current research interests include multi-dimensional and statistical signal processing and their applications to inverse problems in imaging and sensor array signal processing, and to diagnostic and scientific visualization.

 

Thomas S. Huang

Professor Huang is co-chair of the Human-Computer Intelligent Interaction Laboratory. The main research theme of the lab is to enhance human-machine interface design through the optimization of state-of-the-art technology development and engineering of multimodal interface design concepts.

Pierre Moulin

Professor Moulin's research involves the development of novel methods for modeling and processing signals, images, and video, with a focus on problems of compression, restoration, and, more recently, information hiding and authentication. Applications of interest include videoconferencing, digital TV, multimedia services, and computed imaging.

Machine Vision for Improved Safety Inspection of Railcars

funded by the Transportation Research Board

Distributed Control for Large Telescopic Systems

In this project, we are studying and developing distributed control methods for the primary mirror of large segmented telescopes. The aim is to determine the limits of imaging accuracy that can be achieved by the use of closed-loop control of the individual mirror segments. Wind disturbances and structural couplings play a major role in limiting the position accuracy of such large structures.

Fast Scanning and Fast Image Reconstruction in Atomic Force Microscopy

funded by the Air Force Office of Scientific Research

Efficient Algorithms for Lossless Data and Image Compression

funded by the National Science Foundation

Machine-Vision Based Assessment of Intermodal Railroad Loading Patterns

funded by the Burlington Northern Santa Fe

Automated Visual Learning of Safety Appliances on Railcars

funded by the American Association for Railroads