Multi-Task Handwritten Document Layout Analysis

Abstract

Document Layout Analysis is a fundamental step in Handwritten Text Processing systems, from the extraction of the text lines to the type of zone it belongs to. We present a system based on artificial neural networks which is able to determine not only the baselines of text lines present in the document, but also performs geometric and logic layout analysis of the document. Experiments in three different datasets demonstrate the potential of the method and show competitive results with respect to state-of-the-art methods.

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Cited by in corpus (4)

• DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition
• BADAM: A Public Dataset for Baseline Detection in Arabic-script Manuscripts
• Evaluation of a Region Proposal Architecture for Multi-task Document Layout Analysis
• Digital Editions as Distant Supervision for Layout Analysis of Printed Books