SHIBR—The Swedish Historical Birth Records: a semi-annotated dataset

• Tác giả: Cheddad, Abbas ; Kusetogullari, Hüseyin ; Hilmkil, Agrin ; Sundin, Lena ; Yavariabdi, Amir ; Aouache, Mustapha ; Hall, Johan
• Chủ đề: Algorithms ; Archives & records ; Artificial Intelligence ; Columns (structural) ; Computational Biology/Bioinformatics ; Computational Science and Engineering ; Computer Science ; Data mining ; Data Mining and Knowledge Discovery ; Datasets ; Digital imaging ; Handwriting ; Historical data of birth recordsHandwritten documentsPublic datasetWord spotting ; Image Processing and Computer Vision ; Image resolution ; Machine learning ; Original Article ; Probability and Statistics in Computer Science
• Là 1 phần của: Neural computing & applications, 2021-11, Vol.33 (22), p.15863-15875
• Mô tả: This paper presents a digital image dataset of historical handwritten birth records stored in the archives of several parishes across Sweden, together with the corresponding metadata that supports the evaluation of document analysis algorithms’ performance. The dataset is called SHIBR (the Swedish Historical Birth Records). The contribution of this paper is twofold. First, we believe it is the first and the largest Swedish dataset of its kind provided as open access (15,000 high-resolution colour images of the era between 1800 and 1840). We also perform some data mining of the dataset to uncover some statistics and facts that might be of interest and use to genealogists. Second, we provide a comprehensive survey of contemporary datasets in the field that are open to the public along with a compact review of word spotting techniques. The word transcription file contains 17 columns of information pertaining to each image (e.g., child’s first name, birth date, date of baptism, father's first/last name, mother’s first/last name, death records, town, job title of the father/mother, etc.). Moreover, we evaluate some deep learning models, pre-trained on two other renowned datasets, for word spotting in SHIBR. However, our dataset proved challenging due to the unique handwriting style. Therefore, the dataset could also be used for competitions dedicated to a large set of document analysis problems, including word spotting.
  
• Nơi xuất bản: London: Springer London
  
• Ngôn ngữ: English
  
• Số nhận dạng: ISSN: 0941-0643
  ISSN: 1433-3058
  EISSN: 1433-3058
  DOI: 10.1007/s00521-021-06207-z
  
• Nguồn: SpringerOpen
  AUTh Library subscriptions: ProQuest Central
  SWEPUB Freely available online