EventsMOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Event submissions
Published
with-doi10.3390/mol2net-06-06898 (registering DOI)
This submission belongs to the session 08. TECHLAWSCI-04: PANELFIT & NKL H2020 Tech. Law. & Sci. Challenges, Bilbao, Spain, Halden, Norway, Baltimore, USA, 2020 of the event MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed.
Published date
30 Aug, 2020
Citation
Bernabe Ortega-Tenezaca, Viviana Quevedo-Tumailli, Edgar Rivadeniera-Ramos, Luis Alberto Uvidia Armijo, Vision IA Microservice for the detection of ID personal data, in Proceedings of MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed., 30 January 2020–30 January 2021, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-06-06898
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Vision IA Microservice for the detection of ID personal data

image
Bernabe Ortega-Tenezaca 1,2
Viviana Quevedo-Tumailli 3,4
Edgar Rivadeniera-Ramos 5
Luis Alberto Uvidia Armijo 6
1. RNASA-IMEDIR, Computer Science Faculty, University of A Coruña, 15071, A Coruña, Spain., Ecuador
2. Universidad Estatal Amazónica – Puyo, Pastaza, Ecuador.
3. RNASA-IMEDIR, Computer Science Faculty, University of A Coruña, 15071, A Coruña, Spain.
4. Universidad Estatal Amazónica, Sciences of Earth Departament, Puyo, Ecuador
5. Universidad Estatal de Bolívar, DTIC; Bolívar, Ecuador
6. Escuela Superior Politécnica de Chimborazo, Riobamba, Chimborazo, Ecuador.
Abstract

We provided a microservice developed in Nodejs connected to Google Cloud services. From a photograph of the ID obtained through a mobile device, its content is analyzed to extract its information. The Vision AI API uses AutoML Vision, which is capable of interpreting text. The information returned by the Vision AI service is processed in the microservice and the confidential information is anonymized, to be stored in a MySQL database server. The microservice is part of a mobile application to register the entry of citizens to a government institution.

Keywords
AutoML
Vision
Text detection
Manuscript
Mol2net-04-2020.pdf
Poster
Mol2net-04-2020.pdf
Mol2net-04-2020.pdf
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