Important applications related to PRIP Lab research include face recognition, fingerprint identification, document image analysis, 3D object recognition, robot navigation, and visualization/exploration of 3D data.
PRIP Lab faculty and students investigate the use of machines to recognize a variety of patterns or objects. Methods are developed to sense objects, to discover which of their features distinguish them from others, and to design algorithms that can be used by a machine to classify or cluster objects. Since many applications use a sensed image to initially represent the object much PRIP Lab research deals with images. A significant portion of our research focuses on the development of algorithms to do feature extraction (such as finding the ends of ridges in a fingerprint) and matching (such as matching ridge endpoints across two fingerprints) and on the organization of data to support efficient matching.
Some recent projects include biometric authentication, automatic surveillance and tracking of people in a work area, face modeling, digital watermarking, medical image segmentation, and analyzing structure of online documents. Description of both current and recent research projects can be found under research from http://www.cse.msu.edu/prip/General/