An Automatic Reader of Identity Documents
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Abstract (arXiv)
Identity documents automatic reading and verification is an appealing technology for nowadays service industry, since this task is still mostly performed manually, leading to waste of economic and time resources. In this paper the prototype of a novel automatic reading system of identity documents is presented. The system has been thought to extract data of the main Italian identity documents from photographs of acceptable quality, like those usually required to online subscribers of various services. The document is first localized inside the photo, and then classified; finally, text recognition is executed. A synthetic dataset has been used, both for neural networks training, and for performance evaluation of the system. The synthetic dataset avoided privacy issues linked to the use of real photos of real documents, which will be used, instead, for future developments of the system.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jun 2020.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 1.
4 papers.
- 2021MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysiscited by 32
- 2024DocXPand-25k: a large and diverse benchmark dataset for identity documents analysiscited by 5
- 2021Advanced Hough-based method for on-device document localizationcited by 4
- 2021Towards an Efficient Semantic Segmentation Method of ID Cards for Verification Systemscited by 3
- 2024DocXPand-25k: a large and diverse benchmark dataset for identity documents analysis30 Jul 2024
- 2021Towards an Efficient Semantic Segmentation Method of ID Cards for Verification Systems24 Nov 2021
- 2021MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysis1 Jul 2021
- 2021Advanced Hough-based method for on-device document localization18 Jun 2021