Heinz Miklas

Ancient document analysis based on text line extraction

In order to preserve our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents. In the case of degraded manuscripts (e.g. by mold, humidity, bad storage conditions) the text or parts of it can disappear. The remaining parts of the text can be segmented and the ruling can be extrapolated with the a priori knowledge. Since the ruling defines the position of the text within a page, it can be used for layout analysis and as a basis for the enhancement of the readability. Furthermore, information about the scribe (hand) of the manuscript, its spatiotemporal origin can be gained by analyzing the ruling. This paper presents an algorithm for ruling estimation of Glagolitic texts based on text line extraction and is suitable for degraded manuscripts by extrapolating the baselines with the a priori knowledge of the ruling. The algorithm was tested on 30 pages of the Missale Sinaiticum and the evaluation was based on visual criteria.

Contrast Enhancement in Multispectral Images by Emphasizing Text Regions

This paper deals with the enhancement of the readability in historic texts written on parchment. Due to mold, air, humidity, water, etc. parchment and text are partially damaged and consequently hard to read. In order to enhance the readability of the text, the manuscript pages are imaged in different spectral bands ranging from 360 to 1000 nm. The readability enhancement is based on a spectral and spatial analysis of the multivariate image data by multivariate spatial correlation. The main advantage of the method is that especially the text regions are enhanced which is provided by generating a mask image. This mask is based on the automatic reconstruction of the ruling scheme of the text pages. The method is tested on two medieval Slavonic manuscripts written on parchment.

Image Acquisition & Processing Routines for Damaged Manuscripts

This paper presents an overview of data acquisition and processing procedures of an interdisciplinary project of philologists and image processing experts aiming at the decipherment and reconstruction of damaged manuscripts. The digital raw image data was acquired via multi-spectral imaging. As a preparatory step we developed a method of foreground-background separation (binarisation) especially designed for multi-spectral images of degraded documents. On the basis of the binarised images further applications were developed: an automatic character decomposition and primitive extraction dissects the scriptural elements into analysable pieces that are necessary for palaeographic and graphemic analyses, writing tool recognition, text restoration, and optical character recognition. The results of the relevant procedures can be stored and interrogated in a database application. Furthermore, a semi-automatic page layout analysis provides codicological information on latent page contents (script, ruling, decorations).