Semiautomatic Text Baseline Detection in Large Historical Handwritten Documents

Analysis of handwritten documents is a challenging task in the modern era of document digitization. It requires efficient preprocessing which includes word segmentation and baseline detection. This paper proposes a novel approach toward word segmentation and baseline detection in a handwritten document. It is based on certain structural properties of isothetic covers tightly enclosing the words in a handwritten document. For an appropriate grid size, the isothetic covers successfully segregate the words so that each cover corresponds to a particular word. The grid size is selected by an adaptive technique that classifies the inter-cover distances into two classes in an unsupervised manner. Finally, by using a geometric heuristic with the horizontal chords of these covers, the corresponding baselines are extracted. Owing to its traversal strategy along the word boundaries in a combinatorial manner and usage of limited operations strictly in the integer domain, the method is found to be quite fast, efficient, and robust, as demonstrated by experimental results with datasets of both Bengali and English handwritings.

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Multi-task Layout Analysis for Historical Handwritten Documents Using Fully Convolutional Networks

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2018/147 ◽

2018 ◽

Cited By ~ 5

Author(s):

Yue Xu ◽

Fei Yin ◽

Zhaoxiang Zhang ◽

Cheng-Lin Liu

Keyword(s):

Document Image ◽

Text Line ◽

Layout Analysis ◽

Page Segmentation ◽

Handwritten Documents ◽

The Public ◽

Convolutional Networks ◽

Fully Convolutional Networks ◽

Baseline Detection ◽

Line Segmentation

Layout analysis is a fundamental process in document image analysis and understanding. It consists of several sub-processes such as page segmentation, text line segmentation, baseline detection and so on. In this work, we propose a multi-task layout analysis method that use a single FCN model to solve the above three problems simultaneously. The FCN is trained to segment the document image into different regions and detect the center line of each text line by classifying pixels into different categories. By supervised learning on document images with pixel-wise labels, the FCN can extract discriminative features and perform pixel-wise classification accurately. After pixel-wise classification, post-processing steps are taken to reduce noises, correct wrong segmentations and find out overlapping regions. Experimental results on the public dataset DIVA-HisDB containing challenging medieval manuscripts demonstrate the effectiveness and superiority of the proposed method.

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Baseline Detection on Arabic Handwritten Documents

Proceedings of the 2017 ACM Symposium on Document Engineering - DocEng '17 ◽

10.1145/3103010.3121037 ◽

2017 ◽

Cited By ~ 2

Author(s):

Ahmed Fawzi ◽

Moisés Pastor ◽

Carlos D. Martínez-Hinarejos

Keyword(s):

Handwritten Documents ◽

Baseline Detection

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Unknown Documents of 1734 About Swedish Citizens Taken Into Serfdom

SUMY HISTORICAL AND ARCHIVAL JOURNAL ◽

10.21272/shaj.2019.i32.p.12 ◽

2019 ◽

pp. 12-19

Author(s):

Serhii I. Degtyarev ◽

Violetta S. Molchanova

Keyword(s):

Social History ◽

Russian Empire ◽

District Court ◽

Peace Agreement ◽

The Caucasus ◽

Handwritten Documents ◽

Ancient Times ◽

Historical Phenomenon ◽

State Archives ◽

The Russian Empire

This work is devoted to the publication and analysis of two previously unknown handwritten documents of 1734. These documents contain information on several persons of Swedish nationality, which were illegally taken out by the Russian nobleman I. Popov during the Northern War from the territory of Sweden. Materials are stored in the State Archives of the Sumy region. They are part of the archival case of Okhtyrka District Court, but they are not thematically connected with it. These documents were once part of a much larger complex of materials. They refer to the request of former Swedish nationals to release them from serfdom from the Belgorod and Kursk landlords Popov and Dolgintsev. The further fate of these people remained unknown. But it is known that they were mistreated by their masters. Russian legislation at the time prohibited such treatment of persons of Swedish nationality. This was discussed in terms of the peace agreement Nishtadskoyi 1721. The two documents revealed illustrate the episodes of the lives of several foreigners who were captured. The analyzed materials give an opportunity to look at a historical phenomenon like a serfdom in the territory of the Russian Empire under a new angle. They allow us to study one of the ways to replenish the serfs. Documents can also be used as a source for the study of some aspects of social history, in biographical studies. The authors noted that the conversion to the property of the enslaved people of other nationalities was a very common practice in the XVII-XIX centuries. This source of replenishment of the dependent population groups were popular in many nations in Europe, Asia and Africa since ancient times. For example, in the Crimean Khanate, Turkey, Italy, Egypt, the nations of the Caucasus and many others. Кeywords: Sweden, Russian Empire, historical source, documents, Russo-Swedish War, Nistadt Treaty, Viborg, Swedish citizens, enslavement, serfdom.

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A Multimodal Crowdsourcing Framework for Transcribing Historical Handwritten Documents

Proceedings of the 2016 ACM Symposium on Document Engineering - DocEng '16 ◽

10.1145/2960811.2960815 ◽

2016 ◽

Cited By ~ 6

Author(s):

Emilio Granell ◽

Carlos-D. Martínez-Hinarejos

Keyword(s):

Handwritten Documents

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Poverty, Philanthropy and Social Conditions in Victorian Britain

The Charleston Advisor ◽

10.5260/chara.22.1.51 ◽

2020 ◽

Vol 22 (1) ◽

pp. 51-55

Author(s):

Dawn Behrend

Keyword(s):

Social Conditions ◽

British Library ◽

Settlement Houses ◽

Handwritten Documents ◽

Victorian Era ◽

Victorian Britain ◽

Handwritten Text ◽

Handwritten Text Recognition ◽

The Uk ◽

Keyword Searching

Poverty, Philanthropy and Social Conditions in Victorian Britain published by Adam Matthew Digital is comprised of primary digital materials culled from three major archives in Britain and the UK focused on the experience of poverty in Victorian Britain and efforts involving economic, government, and social reform such as the Poor Law, workhouses, settlement houses, and philanthropic initiatives. Content is derived from the National Archives at Kew, British Library, and Senate House Library and includes pamphlets, correspondence, newspaper clippings, books, and other resources. A small portion of the collection utilizes Adam Matthew Digital’s Handwritten Text Recognition (HTR) to enable keyword searching of handwritten documents. The digitized images and documents are clear, searchable, and user-friendly to access, save, and share. Contract provisions are standard to the product with authenticated access across institutional locations and guidelines for Interlibrary Loan sharing. Pricing is determined by institutional size and enrollment. While the product is a one-time purchase, annual hosting fees apply for ongoing access. Content is currently heavily derived from one archive, the Senate House Library, with pamphlets from this source making up nearly half of the total holdings. Users seeking access to a more extensive collection of similar material may prefer subscribing to JSTOR which includes JSTOR 19th Century British Pamphlets with over 26,000 pamphlets along with secondary scholarly journals and eBooks on the Victorian era. While not providing the primary sources of Poverty, Philanthropy and Social Conditions in Victorian Britain or JSTOR, Historical Abstracts may be an alternative resource in providing access to notable scholarly resources on the period.

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