Implementation of Content Analysis System for Recognition of Journals＇ Table of Contents

초록

In this paper, we design the primary component, an automated segmentation method that extracts article titles, author names and page numbers from scanned image of a journal’s table of contents. We expanded the method to five types of journal layout. An interactive tool was also developed with Visual C++ to help the user manage the segmentation results, and manually control the table analysis. Its performance was tested over a panel of seventy images, which gather the most common types of layout encountered