The music scores of 18th century and early were produced only in manual way. The important problem of the current registration of old historical music scores lays in the identification of corresponding writer, that means to estimate who did the notation write or draw. We are developing an efficient identification of a writer's hand. This identification is based on the automated image analysis approach. The theoretical manual identification is been developing at the Institute for Musicology at the University of Rostock. First tests of an analogue approach were applied on chosen music notations. These tests indicate that the recognition problem can be sufficiently solved only by computeraided assistance. Our research activities are concentrated on the development of an automated identification of writers by analysing of notation graphic features. In our article we describe an approach for the automated image analysis and understanding as applied to digitised music scores. This approach is aimed to solve the automated identification of writers as a result of digital music notation matching.

Archiving, processing, and intelligent retrieval of digital video sequences can be efficiently solved by a high-level representation of video sequences. We describe a complete system for encoding the contents of video sequences based on their syntactical and semantical description. Our techniques are built on two phases: analysis and synthesis. The analysis phase involves the automatic generation of a syntactical structure using image and imagesequence analysis, image understanding as well as text recognition. Moreover, the syntactical description of images will be completed by a semantical understanding of video sequences. The full representation of video sequences will be generated during the synthesis phase by combining results from the analysis phase. Our developed prototype system is planned to be integrated into the cooperative work of a TV-team of the TV-station "Radio Bremen". Additionally, we describe some special functionality: scene analysis by clustering of video sequences with the aim of identifying a typical video genre. The latter is an useful approach for automatic trailer generation and for intelligent video editing as add-on for a video-cut-system.

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