Scanned Documents Metadata Generation Database Word Spotting Origin Identification Browsing Writing Classification Book Search Data Retrieval Palaeography Codicology Text Analysis Segmentation Annotation Transcription Denoising Binarization Image Preprocessing Processing Applications

Recently, many big libraries all over the world have been scanning their collections to make them publicly available and to preserve historical documents. We present a modular software system which can be used as a tool for semi-automatical processing of historical handwritten Arabic documents. The development of this system is part of the HADARA project which aims for historical document analysis of Arabic manuscripts and consists of a project team including engineers and computer scientists but also users such as linguists and historians. The HADARA system is designed to support script and content analysis, identification, and classification of historical Arabic documents. The system has been created following an iterative development approach, and the current version assists the user in an interactive and partially already in an automatic manner. In this paper, a system overview is given and the first modules are presented which support the annotation of a scanned manuscript in a semi-automatic manner. They comprise page layout analysis, text line segmentation, and transcription. Word spotting is the first application implemented in the HADARA system and its concept is outlined in this paper. Introduction Nowadays, there is a trend to digitize printed or handwritten historical documents in many big libraries all over the world. Scanned images are published on library websites after manually adding metadata information. This information provides the ability to search for a specific document in a large database. Unfortunately, searching through the content of a document is not possible as long as the content itself is not digitally available in a textual form. However, a manual transcription requires large efforts in terms of time and costs. To overcome these limitations computer scientists and researchers in the field of document analysis and recognition develop algoritms for an automatic transcription of scanned historical documents or at least to support specific parts of this task. Pattern recognition methods, such as automatic text recognition or word spotting, are employed for this purpose. On the one hand, large scale digitization projects are underway at most big libraries and even private companies (e. g., Million Book Project [1] or Google Book Search [2]) to preserve paper documents in digital format. On the other hand, many researchers all over the world work on projects for historical document processing and recognition, as can be seen at conferences like ICDAR [3] , ICFHR [4], or DAS [5], workshops like HIP [6], and research projects like IMPACT [7]. The cooperation of exFigure 1. Example pages of a scanned Arabic handwritten book with side notes1 perts from digitization projects and researchers from the field of document analysis and recognition is gaining importance. For example, the very time consuming and expensive task of the generation of training data for recognition tasks can benefit from cooperation of librarians and computer scientists. Typical pages of an Arabic handwritten book written in the 18th century (the text dates back to the 12th century) are shown in Figure 1. In the center of each page the main body text is written, additionally comments and remarks are written on the page borders. These are added usually neither from the same writer nor from the same period as the main body text. This example shows one of the major problems for interpretation of historical Arabic manuscripts. An overview about the challenges of historical document processing is given in [8]. The HADARA project team consists of scientists from signal processing, computer science, science of history, and linguistics. The diversity inside this group ensures that the different needs of the involved areas of expertise are respected during the whole development process. The core of the HADARA system consists of an easy-to-use historical document processing tool chain 1Scan provided by the Damascene family library Refaiya at the University Library in Leipzig, Germany, Website: http://www.refaiya. unileipzig.de/ Scanned Documents Metadata Generation Database Word Spotting Origin Identification Browsing Writing Classification Book Search Data Retrieval Palaeography Codicology Text Analysis Segmentation Annotation Transcription Denoising Binarization Image Preprocessing Processing