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International Journal on Document Analysis and Recognition (IJDAR) OnlineFirst articles

21-07-2021 | Special Issue Paper

Beyond document object detection: instance-level segmentation of complex layouts

Information extraction is a fundamental task of many business intelligence services that entail massive document processing. Understanding a document page structure in terms of its layout provides contextual support which is helpful in the …

Authors:
Sanket Biswas, Pau Riba, Josep Lladós, Umapada Pal

14-07-2021 | Original Paper

MRZ code extraction from visa and passport documents using convolutional neural networks

Detecting and extracting information from the machine-readable zone (MRZ) on passports and visas is becoming increasingly important for verifying document authenticity. However, computer vision methods for performing similar tasks, such as optical …

Authors:
Yichuan Liu, Hailey James, Otkrist Gupta, Dan Raviv

08-07-2021 | Special Issue Paper

Revealing a history: palimpsest text separation with generative networks

A palimpsest is a historical manuscript in which the original text (termed under-text) was erased and overwritten with another script in order to recycle the parchment. One of the main challenges in studying palimpsests is to reveal the …

Authors:
Anna Starynska, David Messinger, Yu Kong

30-06-2021 | Original Paper

Extracting text from scanned Arabic books: a large-scale benchmark dataset and a fine-tuned Faster-R-CNN model

Datasets of documents in Arabic are urgently needed to promote computer vision and natural language processing research that addresses the specifics of the language. Unfortunately, publicly available Arabic datasets are limited in size and …

Authors:
Randa Elanwar, Wenda Qin, Margrit Betke, Derry Wijaya

24-06-2021 | Special Issue Paper

EAML: ensemble self-attention-based mutual learning network for document image classification

In the recent past, complex deep neural networks have received huge interest in various document understanding tasks such as document image classification and document retrieval. As many document types have a distinct visual style, learning only …

Authors:
Souhail Bakkali, Zuheng Ming, Mickaël Coustaty, Marçal Rusiñol

21-06-2021 | Original Paper

A hybrid approach to recognize generic sections in scholarly documents

Discourse parsing of scholarly documents is the premise and basis for standardizing the writing of scholarly documents, understanding their content, and quickly locating and extracting specific information from them. With the continuous emergence …

Authors:
Shoubin Li, Qing Wang

14-06-2021 | Special Issue Paper

Data Augmentation using Geometric, Frequency, and Beta Modeling approaches for Improving Multi-lingual Online Handwriting Recognition

The lack of large training data in the context of deep learning applications is a serious issue investigated by many studies that deal with the current challenge. In this paper, we introduce new data augmentation methods that generate more shape …

Authors:
Yahia Hamdi, Houcine Boubaker, Adel M. Alimi

11-06-2021 | Special Issue Paper

Learning from similarity and information extraction from structured documents

The automation of document processing has recently gained attention owing to its great potential to reduce manual work. Any improvement in information extraction systems or reduction in their error rates aids companies working with business …

Author:
Martin Holeček

11-06-2021 | Special Issue Paper

A two-step framework for text line segmentation in historical Arabic and Latin document images

One of the most important preliminary tasks in a transcription system of historical document images is text line segmentation. Nevertheless, this task remains complex due to the idiosyncrasies of ancient document images. In this article, we …

Authors:
Olfa Mechi, Maroua Mehri, Rolf Ingold, Najoua Essoukri Ben Amara

10-06-2021 | Original Paper

SKFont: skeleton-driven Korean font generator with conditional deep adversarial networks

In our research, we study the problem of font synthesis using an end-to-end conditional deep adversarial network with a small sample of Korean characters (Hangul). Hangul comprises of 11,172 characters and is composed by writing in multiple …

Authors:
Debbie Honghee Ko, Ammar Ul Hassan, Jungjae Suk, Jaeyoung Choi

08-06-2021 | Special Issue Paper

Self-supervised deep metric learning for ancient papyrus fragments retrieval

This work focuses on document fragments association using deep metric learning methods. More precisely, we are interested in ancient papyri fragments that need to be reconstructed prior to their analysis by papyrologists. This is a challenging …

Authors:
Antoine Pirrone, Marie Beurton-Aimar, Nicholas Journet

23-05-2021 | Original Paper

TextPolar: irregular scene text detection using polar representation

How to precisely detect arbitrary-shaped texts in natural images has recently become a new hot topic in areas of computer vision and pattern recognition. However, the performance of most existing methods is still unsatisfactory mainly due to the …

Authors:
Jie Chen, Zhouhui Lian

21-05-2021 | Original Paper

Segmentation of text lines using multi-scale CNN from warped printed and handwritten document images

Paper documents are ideal sources of useful information and have a profound impact on every aspect of human lives. These documents may be printed or handwritten and contain information as combinations of texts, figures, tables, charts, etc. This …

Authors:
Arpita Dutta, Arpan Garai, Samit Biswas, Amit Kumar Das

19-05-2021 | Special Issue Paper Open Access

Learning-free pattern detection for manuscript research:

An efficient approach toward making manuscript images searchable

Automatic pattern detection has become increasingly important for scholars in the humanities as the number of manuscripts that have been digitised has grown. Most of the state-of-the-art methods used for pattern detection depend on the …

Authors:
Hussein Mohammed, Volker Märgner, Giovanni Ciotti