Segmentierung und Klassifizierung von Bildern und Bildsequenzen mit Hidden-Markov-Modellen - Segmentation and Classification of Images and Image Sequences Using Hidden Markov Models
The thesis presents a novel rotation-invariant modeling technique of pictograms and planar objects using conventional one-dimensional Hidden-Markov-Models. To verify the proposed approach, experiments with an image database system have been carried out, where users are enabled to provide simple sketches in order to retrieve images from the database. Thereafter, a statistical approach is presented, which allows the spotting and classification of two-dimensional patterns in complex scenes. Finally, novel pseudo three-dimensional HMMs are introduced, which allow the recognition of image sequences.
Many experiments utilizing the novel modeling techniques are described in this theses. The achieved results demonstrate that the approaches can be used to solve problems in man-machine-communication as well as multimedia applications. Thus, the huge application potential of HMMs for image and image sequence recognition is shown.
Advisor:Prof. Dr. Heinrich Müller; Prof. Dr.-Ing. habil. Gerhard Rigoll
Source Type:Master's Thesis
Keywords:elektrotechnik gerhard mercator universitaet
Date of Publication:05/16/2002