Handwriting recognition in historical documents is vital for the creation of digital libraries. The creation of readily available ground truth data plays a central role for the development of new recognition technologies. For historical documents, ground truth creation is more difficult and timeconsuming when compared with modern documents. In this paper, we present a semi-automatic ground truth creation proceeding for historical documents that takes into account noisy background and transcription alignment. The proposed ground truth creation is demonstrated for the IAM Historical Handwriting Database (IAM-HistDB) that is currently under construction and will include several hundred Old German manuscripts. With a small set of algorithmic tools and few manual interactions, it is shown how laypersons can efficiently create a ground truth for handwriting recognition.
In this paper we propose a novel approach to the detection of on-line handwritten text lines based on dynamic programming. We try to find the paths with the minimum cost between two consecutive text lines. Most steps of the proposed algorithm are based on off-line information. Hence the method can also be applied to off-line documents after a few minor changes. In our experiments we show that this dynamic programming based approach is better than a common on-line segmentation procedure.
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