[Paper Review] LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books

Christian Reul, Uwe Springmann+1 more|arXiv (Cornell University)|Jan 20, 2017

Handwritten Text Recognition Techniques5 references4 citations

TL;DR

LAREX is a semi-automatic, open-source tool for layout analysis and region extraction in early printed books, using a rule-based connected components approach for fast, intuitive segmentation. It supports PageXML integration, enabling efficient OCR workflow compatibility, and delivers accurate, flexible page segmentation with minimal user intervention.

ABSTRACT

A semi-automatic open-source tool for layout analysis on early printed books is presented. LAREX uses a rule based connected components approach which is very fast, easily comprehensible for the user and allows an intuitive manual correction if necessary. The PageXML format is used to support integration into existing OCR workflows. Evaluations showed that LAREX provides an efficient and flexible way to segment pages of early printed books.

Motivation & Objective

• To address the challenge of accurately segmenting complex layouts in early printed books, which often feature irregular typography, ornate decorations, and degraded text.
• To develop a fast, transparent, and user-friendly tool that supports both automated processing and manual correction for improved segmentation accuracy.
• To enable seamless integration into existing OCR pipelines through standardized PageXML format support.
• To provide a flexible, extensible solution for researchers and cultural heritage institutions working with historical digitized texts.
• To reduce manual annotation effort while maintaining high segmentation quality on challenging historical document images.

Proposed method

• LAREX employs a rule-based connected components analysis to identify and group text and non-text regions in early printed book pages.
• The method leverages morphological operations and geometric heuristics to distinguish between text blocks, illustrations, and decorative elements.
• It supports interactive correction via a graphical user interface, allowing users to refine segmentation results manually.
• Output is generated in the PageXML format, ensuring compatibility with downstream OCR and text processing tools.
• The tool is implemented as open-source software, enabling community contributions and deployment in diverse research and institutional settings.
• The approach is designed for efficiency and interpretability, avoiding complex machine learning models that require large annotated datasets.

Experimental results

Research questions

• RQ1 How can layout analysis in early printed books be performed efficiently while maintaining high accuracy?
• RQ2 To what extent can a rule-based approach outperform or complement learning-based methods on historical documents with complex layouts?
• RQ3 Can a semi-automatic tool with manual correction capabilities significantly reduce user effort while ensuring reliable segmentation?
• RQ4 How well does the PageXML output from LAREX integrate into existing OCR and text processing workflows?
• RQ5 What is the performance of LAREX in segmenting diverse layout types found in early printed books, such as multi-column text, marginalia, and woodcut illustrations?

Key findings

• LAREX achieves fast and accurate layout segmentation on early printed books using a rule-based, connected components approach.
• The tool enables efficient manual correction, significantly reducing the time required for error correction compared to fully manual methods.
• PageXML output from LAREX is compatible with standard OCR tools, facilitating integration into existing digital humanities and archival workflows.
• Evaluations demonstrate that LAREX provides a flexible and reliable solution for segmenting complex historical document layouts.
• The open-source nature of LAREX supports extensibility and adoption by cultural heritage institutions and research communities.
• The method is particularly effective for documents with consistent typographic features, though performance may vary on highly degraded or irregularly formatted pages.