This paper presents an efficient approach to identify tabular structures within either electronic or paper documents. The resulting T-Recs system takes word bounding box information as input, and outputs the corresponding logical text block units. Starting with an arbitrary word as block seed the algorithm recursively expands this block to all words that interleave with their vertical neighbors. Since even smallest gaps of table columns prevent their words from mutual interleaving, this initial segmentation is able to identify and isolate such columns. In order to deal with some inherent segmentation errors caused by isolated lines, overhanging words, or cells spawning more than one column, a series of postprocessing steps is added. These steps benefit form a very simple distinction between type 1 and type 2 blocks: type 1 blocks are those of at most one word per line, all others are of type 2. This distinction allows the selective application of heuristics to each group of blocks. The conjoint decomposition of column blocks into subsets of table cells leads to the final block segmentation of a homogeneous abstraction level. These segments serve the final layout analysis which identifies table environments and cells that are stretching over several rows and/or columns.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Table structure recognition based on robust block segmentation

This paper presents a new approach to table structure recognition as well as to layout analysis The discussed recognition process differs significantly from existing approaches as it realizes a bottom-up clustering of given word segments, whereas conventional table structure recognizers all rely on the detection of some separators such as delineation or significant white space to analyze a page from the top-down The following analysis of the recognized layout elements is based on the construction of a tile structure and detects row- and/or column spanning cells as well as sparse tables with a high degree of confidence

The overall system is completely domain independent, optionally neglects textual contents and can thus be applied to arbitrary mixed-mode documents (with or without tables) of any language and even operates on low quality OCR documents (eg facsimiles)

/pdf/the-t-recs-table-recognition-and-analysis-system-44mfeafz5r.pdf

The T-Recs Table Recognition and Analysis System

Systems and methods for automatically extracting form information (document structure, elements, format, etc.) from electronic documents such as raster-based passive documents, and storing such form information in a file in accordance with a predetermined DTD (document type definition).

Systems and methods for automatic form segmentation for raster-based passive electronic documents

Review article: A review of structured document retrieval (SDR) technology to improve information access performance in engineering document management

Together with the rapidly growing amount of online data, we register an immense need for intelligent search engines that access a restricted amount of data as found in intranets or other limited domains. These sorts of search engine must go beyond simple keyword indexing/matching, but they also have to be easily adaptable to new domains without huge costs. The paper presents a mechanism that addresses both of these points: first of all, the internal document structure is being used to extract concepts which impose a directory-like structure on the documents, similar to those found in classified directories. Furthermore, this is done in an efficient way which is largely language independent and does not make assumptions about the document structure.

Exploiting structure for intelligent Web search

We report on the design and implementation of a system which automates the process of capturing structured documents from the optically recognized form of printed materials. The system is intended to be used to convert printed collections into their corresponding tagged electronic versions with little or no manual interventon. This conversion process has some unique problems associated with it, these are discussed, along with our attempts to solve them. This system also establishes a mapping between the bitmap image and its corresponding ASCII representation that can be used to design flexible image-based interfaces for IR-related applications.

/pdf/aototag-a-tool-for-creating-structured-document-collections-3zn5izb9ho.pdf

Aototag: A Tool for Creating Structured Document Collections from Printed Materials

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Aototag: A Tool for Creating Structured Document Collections from Printed Materials