Efficient indexing and retrieval of digital video is an important function of video databases. One powerful index for retrieval is the text appearing in them. It enables content-based browsing. We present our methods for automatic segmentation of text in digital videos. The output is directly passed to a standard OCR software package in order to translate the segmented text into ASCII. The algorithms we propose make use of typical characteristics of text in videos in order to enable and enhance segmentation performance. Especially the inter-frame dependencies of the characters provide new possibilities for their refinement. Then, a straightforward indexing and retrieval scheme is introduced. It is used in the experiments to demonstrate that the proposed text segmentation algorithms together with existing text recognition algorithms are suitable for indexing and retrieval of relevant video sequences in and from a video database. Our experimental results are very encouraging and suggest that these algorithms can be used in video retrieval applications as well as to recognize higher semantics in videos.
Dieser Eintrag ist Teil der Universitätsbibliographie.
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