Page Layout Analysis System for Unconstrained Historic Documents

02/23/2021
by   Oldřich Kodym, et al.
8

Extraction of text regions and individual text lines from historic documents is necessary for automatic transcription. We propose extending a CNN-based text baseline detection system by adding line height and text block boundary predictions to the model output, allowing the system to extract more comprehensive layout information. We also show that pixel-wise text orientation prediction can be used for processing documents with multiple text orientations. We demonstrate that the proposed method performs well on the cBAD baseline detection dataset. Additionally, we benchmark the method on newly introduced PERO layout dataset which we also make public.

READ FULL TEXT

page 4

page 7

page 11

page 14

05/09/2017

READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival Documents

Text line detection is crucial for any application associated with Autom...
10/22/2018

Baseline Detection in Historical Documents using Convolutional U-Nets

Baseline detection is still a challenging task for heterogeneous collect...
08/26/2021

LayoutReader: Pre-training of Text and Layout for Reading Order Detection

Reading order detection is the cornerstone to understanding visually-ric...
02/09/2018

A Two-Stage Method for Text Line Detection in Historical Documents

This work presents a two-stage text line detection method for historical...
08/22/2018

Hierarchical Neural Network for Extracting Knowledgeable Snippets and Documents

In this study, we focus on extracting knowledgeable snippets and annotat...
07/28/2014

A Fast Hierarchical Method for Multi-script and Arbitrary Oriented Scene Text Extraction

Typography and layout lead to the hierarchical organisation of text in w...
03/28/2022

Towards End-to-End Unified Scene Text Detection and Layout Analysis

Scene text detection and document layout analysis have long been treated...