BH2M: The Barcelona Historical, Handwritten Marriages Database

Fernandez-Mota, David; Almazán, Jon; Cirera, Núria; Fornés, Alícia; Lladós, Josep

doi:10.1109/icpr.2014.53

Cited by 30 publications

(19 citation statements)

References 27 publications

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“…The first dataset is the Barcelona Historical Handwritten Marriages database (BH2M) [13]. It is comprised of a book of marriage licenses, 174 pages long, written between 1617 and 1619 by a single author in old Catalan.…”

Section: Methodsmentioning

confidence: 99%

Visualizing Document Image Collections Using Image-Based Word Clouds

Wilkinson

Brun

2015

Advances in Visual Computing

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Visualizing document image collections using image-based word clouds.In: Advances in Visual Computing: 11th International Symposium, ISVC 2015, Las Vegas, NV, USA, December 14-16, 2015 Abstract. In this paper, we introduce image-based word clouds as a novel tool for a quick and aesthetic overviews of common words in collections of digitized text manuscripts. While OCR can be used to enable summaries and search functionality to printed modern text, historical and handwritten documents remains a challenge. By segmenting and counting word images, without applying manual transcription or OCR, we have developed a method that can produce word or tag clouds from document collections. Our new tool is not limited to any specific kind of text. We make further contributions in ways of stop-word removal, class based feature weighting and visualization. An evaluation of the proposed tool includes comparisons with ground truth word clouds on handwritten marriage licenses from the 17th century and the George Washington database of handwritten letters, from the 18th century. Our experiments show that image-based word clouds capture the same information, albeit approximately, as the regular word clouds based on text data.

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Section: Methodsmentioning

confidence: 99%

Visualizing Document Image Collections Using Image-Based Word Clouds

Wilkinson

Brun

2015

Advances in Visual Computing

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“…This is a time-consuming and tedious process. There are a few datasets available that can be used for manuscript author identification; [7,10,19,20] are some of the major ones. Table 2 shows these datasets and their information.…”

Section: Dataset Descriptionmentioning

confidence: 99%

KERTAS: dataset for automatic dating of ancient Arabic manuscripts

Adam

Baig

Al-Maadeed

et al. 2018

IJDAR

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The age of a historical manuscript can be an invaluable source of information for paleographers and historians. The process of automatic manuscript age detection has inherent complexities, which are compounded by the lack of suitable datasets for algorithm testing. This paper presents a dataset of historical handwritten Arabic manuscripts designed specifically to test state-of-the-art authorship and age detection algorithms. Qatar National Library has been the main source of manuscripts for this dataset while the remaining manuscripts are open source. The dataset consists of over 2000 images taken from various handwritten Arabic manuscripts spanning fourteen centuries. In addition, a sparse representation-based approach for dating historical Arabic manuscript is also proposed. There is lack of existing datasets that provide reliable writing date and author identity as metadata. KERTAS is a new dataset of historical documents that can help researchers, historians and paleographers to automatically date Arabic manuscripts more accurately and efficiently.

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“…1) Esposalles dataset from the BH2M Database: A subset of the Barcelona Historical Handwritten Marriages (BH2M) database [15] i.e. the Esposalles dataset [14] is used for experiments.…”

Section: A Datasetmentioning

confidence: 99%

On-the-fly Historical Handwritten Text Annotation

Vats

Hast

2017

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

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The performance of information retrieval algorithms depends upon the availability of ground truth labels annotated by experts. This is an important prerequisite, and difficulties arise when the annotated ground truth labels are incorrect or incomplete due to high levels of degradation. To address this problem, this paper presents a simple method to perform on-the-fly annotation of degraded historical handwritten text in ancient manuscripts. The proposed method aims at quick generation of ground truth and correction of inaccurate annotations such that the bounding box perfectly encapsulates the word, and contains no added noise from the background or surroundings. This method will potentially be of help to historians and researchers in generating and correcting word labels in a document dynamically. The effectiveness of the annotation method is empirically evaluated on an archival manuscript collection from well-known publicly available datasets.

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BH2M: The Barcelona Historical, Handwritten Marriages Database

Cited by 30 publications

References 27 publications

Visualizing Document Image Collections Using Image-Based Word Clouds

Visualizing Document Image Collections Using Image-Based Word Clouds

KERTAS: dataset for automatic dating of ancient Arabic manuscripts

On-the-fly Historical Handwritten Text Annotation

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