Robust Line Detection in Historical Church Registers

For being able to automatically acquire information recorded in church registers and other historical scriptures, the text of such documents needs to be segmented prior to automatic reading. Segmentation of old handwritten scriptures is difficult for two main reasons

Word matching using single closed contours for indexing handwritten historical documents

Effective indexing is crucial for providing convenient access to scanned versions of large collections of historically valuable handwritten manuscripts. Since traditional handwriting recognizers based on optical character recognition (OCR) do not perform well on historical documents, recently a holistic word recognition approach has gained in popularity as an attractive and more straightforward solution (Lavrenko et al. in proc. document Image Analysis for Libraries (DIAL’04), pp. 278–287, 2004). Such techniques attempt to recognize words based on scalar and profile-based features extracted from whole word images. In this paper, we propose a new approach to holistic word recognition for historical handwritten manuscripts based on matching word contours instead of whole images or word profiles. The new method consists of robust extraction of closed word contours and the application of an elastic contour matching technique proposed originally for general shapes (Adamek and O’Connor in IEEE Trans Circuits Syst Video Technol 5:2004). We demonstrate that multiscale contour-based descriptors can effectively capture intrinsic word features avoiding any segmentation of words into smaller subunits. Our experiments show a recognition accuracy of 83%, which considerably exceeds the performance of other systems reported in the literature

Med Brussel som tyngdepunkt?: svensk og finsk sikkerhetspolitikk i det nye Europa

This paper introduces our efforts to create UPX, an XML-based successor to the venerable UNIPEN format for the representation of annotated datasets of online handwriting data. In the first part of the paper, shortcomins of the UNIPEN format are dicussed and the goals of UPX are outlined. Prior work related to UPX in the form of the recently proposed hwDataset representation is presented. The second part of the paper summarizes the status of the UPX effort, in particular, experiments to map UNIPEN elements to hwDataset and InkML and identify potential issues with migrating existing UNIPEN data to UPX. This is work in progress, and we invite participation from the handwriting recognition research community and industry to make UPX a reality

An XML Representation for Annotated Handwriting Datasets for Online Handwriting Recognition

In this paper, we briefly descibe an XML representation for annotation of online handwriting data to support the development and evaluation of handwriting recognition algorithms, that is based on the emerging Digital Ink Markup Language (InkML) draft standard from W3C. In particular, we describe how the XML representation we have defined attempts to address issues of (i) support for different scripts, (ii) partial automation of labeling using recognition engines, (iii) planned as well as casual capture of handwriting data and (iv) semantic annotation of handwriting data at various levels such as character, word and phrase. The representation keeps the raw handwriting data (described by InkML) separate from its semantic interpretations. We also compare and contrast the XML representation with the extant UNIPEN representation for annotation of handwriting data. 1