Multi-Task Handwritten Document Layout Analysis
This work addresses document layout analysis for handwritten text processing, but it appears incremental as it builds on existing methods with competitive rather than groundbreaking improvements.
The paper tackles the problem of analyzing the layout of handwritten documents, including baseline detection and geometric/logic layout analysis, using artificial neural networks, and reports competitive results on three datasets.
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.