Document analysis at DFKI. - Part 1: Image analysis and text recognition

Document analysis is responsible for an essential progress in office automation. This paper is part of an overview about the combined research efforts in document analysis at the DFKI. Common to all document analysis projects is the global goal of providing a high level electronic representation of documents in terms of iconic, structural, textual, and semantic information. These symbolic document descriptions enable an "intelligent\u27; access to a document database. Currently there are three ongoing document analysis projects at DFKI: INCA, OMEGA, and PASCAL2000/PASCAL+. Though the projects pursue different goals in different application domains, they all share the same problems which have to be resolved with similar techniques. For that reason the activities in these projects are bundled to avoid redundant work. At DFKI we have divided the problem of document analysis into two main tasks, text recognition and text analysis, which themselves are divided into a set of subtasks. In a series of three research reports the work of the document analysis and office automation department at DFKI is presented. The first report discusses the problem of text recognition, the second that of text analysis. In a third report we describe our concept for a specialized document analysis knowledge representation language. The report in hand describes the activities dealing with the text recognition task. Text recognition covers the phase starting with capturing a document image up to identifying the written words. This comprises the following subtasks: preprocessing the pictorial information, segmenting into blocks, lines, words, and characters, classifying characters, and identifying the input words. For each subtask several competing solution algorithms, called specialists or knowledge sources, may exist. To efficiently control and organize these specialists an intelligent situation-based planning component is necessary, which is also described in this report. It should be mentioned that the planning component is also responsible to control the overall document analysis system instead of the text recognition phase onl

Pi_{ODA} : the paper interface to ODA

In the past, many people have proclaimed the vision of the paperless office, but today offices consume more paper documents than ever before. As computer technology becomes more and more important in daily practice of modern offices, intelligent systems bridging the gap between printed documents and electronic ones, called paper-computer-interfaces, are required. In this report our model-based document analysis system Pi_{ODA} is discussed in detail. Basic ideas of the ODA standard for electronic representation of office documents are the foundation of our document model. Moreover, different knowledge sources essential for the analysis of business letters are incorporated into the Pi_{ODA} model. The system comprises all important analysis tasks. Initially, layout extraction includes a necessary low-level image processing and segmentation to investigate the layout structure of a given document. While logical labeling identifies the logical structure of a business letter, text recognition explores the captured text of logical objects in an expectation-driven manner. By this way, word hypotheses are generated and verified using a dictionary. Finally, a partial text analysis component syntactically checks well-structured text objects, primarily the recipient of a letter. As output, Pi_{ODA} produces an ODA conforming symbolic representation of a document originally being captured on paper. Now, the document is available for any further automatic processing such as filing, retrieval or distribution. The inherent modularity of our system, however, allows a reuse of knowledge sources and constituents of the architecture in other document classes such as forms or cheques. Additionally, Pi_{ODA} is an open and flexible system: improved and new analysis methods can be integrated easy without modifying the overall system architecture

TRα2—An Untuned Second Fiddle or Fine-Tuning Thyroid Hormone Action?

Thyroid hormones (THs) control a wide range of physiological functions essential for metabolism, growth, and differentiation. On a molecular level, TH action is exerted by nuclear receptors (TRs), which function as ligand-dependent transcription factors. Among several TR isoforms, the function of TRα2 remains poorly understood as it is a splice variant of TRα with an altered C-terminus that is unable to bind T3. This review highlights the molecular characteristics of TRα2, proposed mechanisms that regulate alternative splicing and indications pointing towards an antagonistic function of this TR isoform in vitro and in vivo. Moreover, remaining knowledge gaps and major challenges that complicate TRα2 characterization, as well as future strategies to fully uncover its physiological relevance, are discussed