Jose Abad Peiro

Identification of document structure and table of content in magazine archives

In this paper, we present a generic approach for reliable identification of the table of content (TOC) pages in scanned documents. We use multiple sources of information to obtain a reliable assessment of the TOC pages and the position of articles. These sources are produced by using three methods: title matching, section keyword matching, and numeric content. Finally a combination component is used to score potential TOC pages and select the best candidates. The system is used to identify the table of content, locate the beginning of articles, aid the process of advertisement identification (where present), and in general, identify the structure of scanned documents for the process of article extraction and online deployment of digital content. Results of applying the algorithms to an 80-years archive of Time weekly magazine are presented.

Document digitization lifecycle for complex magazine collection

The conversion of large collections of documents from paper to digital formats that are suitable for electronic archival is a complex multi-phase process. The creation of good quality images from paper documents is just one phase. To extract relevant information that they contain, with an accuracy that fits the purpose of target applications, an automated document analysis system and a manual verification/review process are needed. The automated system needs to perform a variety of analysis and recognition tasks in order to reach an accuracy level that minimizes the manual correction effort downstream.This paper describes the complete process and the associated technologies, tools, and systems needed for the conversion of a large collection of complex documents and deployment for online web access to its information rich content. We used this process to recapture 80 years of Time magazines. The historical collection is scanned, automatically processed by advanced document analysis components to extract articles, manually verified for accuracy, and converted in a form suitable for web access. We discuss the major phases of the conversion lifecycle and the technology developed and tools used for each phase. We also discuss results in terms of recognition accuracy.