TY - GEN
T1 - A practical approach to validate the authenticity of identity documents
AU - Marin-Aguilar, Ignacio
AU - Chavarria-Zamora, Luis Alberto
AU - Araya-Martinez, Leonardo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - There is a need for a system capable of determining the authenticity of identity documents in a simple way due to the increase over the years of crimes such as fraud and identity theft, this in the specific case of Costa Rica; the reason for this situation is that many processes and transactions can be carried out virtually, which opens the door for this type of crime to take place. For the above purpose, the present work consists of the research, design, and development of a prototype system to determine whether an identification document is authentic. This authenticity estimator consists of a composition of algorithms applied to images, such as filters and transformations; in order to perform a process called Optical Character Recognition (OCR), which consists of the recognition of symbols or characters from a given image. This proposal uses classical computer vision techniques, although it is important to mention that machine learning techniques can also be used for this purpose. Nevertheless, with this approach, 80 percent of accuracy was obtained in the recognition of identity documents.
AB - There is a need for a system capable of determining the authenticity of identity documents in a simple way due to the increase over the years of crimes such as fraud and identity theft, this in the specific case of Costa Rica; the reason for this situation is that many processes and transactions can be carried out virtually, which opens the door for this type of crime to take place. For the above purpose, the present work consists of the research, design, and development of a prototype system to determine whether an identification document is authentic. This authenticity estimator consists of a composition of algorithms applied to images, such as filters and transformations; in order to perform a process called Optical Character Recognition (OCR), which consists of the recognition of symbols or characters from a given image. This proposal uses classical computer vision techniques, although it is important to mention that machine learning techniques can also be used for this purpose. Nevertheless, with this approach, 80 percent of accuracy was obtained in the recognition of identity documents.
KW - Computer Vision
KW - Documents Authenticity
KW - Identity Protection
KW - Image Processing
KW - Optical Character Recognition
KW - Pattern Recognition
UR - http://www.scopus.com/inward/record.url?scp=85141386675&partnerID=8YFLogxK
U2 - 10.1109/LAEDC54796.2022.9908240
DO - 10.1109/LAEDC54796.2022.9908240
M3 - Contribución a la conferencia
AN - SCOPUS:85141386675
T3 - 2022 IEEE Latin America Electron Devices Conference, LAEDC 2022
BT - 2022 IEEE Latin America Electron Devices Conference, LAEDC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Latin America Electron Devices Conference, LAEDC 2022
Y2 - 4 July 2022 through 6 July 2022
ER -