Regularization Techniques in Image Analysis                 (Computer and Information Science)
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Regularization Techniques have been used to solve problems              in stereo vision, shape analysis and motion estimation.  These                  techniques usually incorporate smoothing operations in the                      restoration of degraded images.  They offer a general tool for                  dealing with a variety of problems in image processing and                      computer vision.  While regularization appears to be a very                     promising overall technique, its early applications have suffered               because continuity conditions must be imposed over the whole                    domain of the data.  Clearly, this is not justified in vision                   problems where there is a multitude of objects in a scene, or                   even in a case where there is only one object, but whose surface                is not smooth.  A major goal of this research is to modify                      regularization methods by including discontinuities.  In                        addition, the project will also investigate the applicability of                these methods in textured areas by looking at the statistical                   properties of the data.
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{'Code': '6840', 'Text': 'ROBOTICS'}
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