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Extracción de información de documentos de identidad utilizando técnicas de aprendizaje de máquina

dc.rights.licenseReconocimiento 4.0 Internacional
dc.contributor.advisorVilla Garzón, Fernán Alonso
dc.contributor.authorMárquez Aristizábal, Hugo Alejandro
dc.date.accessioned2022-08-22T21:32:48Z
dc.date.available2022-08-22T21:32:48Z
dc.date.issued2022-06-23
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/82000
dc.description.abstractLa extracción automática de información de documentos de identidad es una tarea fundamental en diferentes procesos digitales como registros, solicitud de productos, validación de identidad, entre otros. La extracción de información consiste en la identificación, ubicación, clasificación y reconocimiento del texto de campos clave presentes en un documento, en este caso un documento de identidad. Tratándose de documentos de identidad, los campos clave son aquellos como: nombres, apellidos, números de documento, fechas, entre otros. El problema de extracción de información se ha solucionado tradicionalmente utilizando algoritmos basados en reglas y motores clásicos de OCR. En los últimos años se han realizado implementaciones de modelos de aprendizaje de máquina, utilizando modelos de NLP (procesamiento de lenguaje natural) y CV (visión por computador) para solucionar el problema de una manera más flexible y eficiente (Subramani et al., 2020). En este trabajo se propuso solucionar el problema de extracción de información con una aproximación de detección de objetos. Se implementó, entrenó y evaluó un modelo de detección de objetos basado en transformadores (Carion et al., 2020). Se logró llegar a una solución que alcanza valores de precisión superiores al 95% en la detección de campos clave en documentos de identidad. (Texto tomado de la fuente)
dc.description.abstractAutomatic information extraction from identity documents is a fundamental task in digital processes such as onboarding, requesting products, identity validation, among others. The information extraction process consists of identifying, locating, classifying and recognizing text of the corresponding key fields that an identity document contains. In the case of identity documents, key fields are: names, last names, document number, dates, among others. The information extraction problem has been traditionally solved using rule based algorithms and classic OCR engines. In the last few years there have been implementations based on machine learning models, using NLP (natural language processing) and CV (computer vision) to solve the problem in a more flexible and efficient way (Subramani et al., 2020). This work proposes to solve the problem of information extraction with an object detection approach. An object detection model based on transformers (Carion et al., 2020) was implemented, trained and evaluated. A solution with above 95% accuracy in detecting key fields on identification documents was achieved.
dc.format.extent67 páginas
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.publisherUniversidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::003 - Sistemas
dc.subject.otherIdentidad digital
dc.subject.otherReconocimiento óptico de caracteres
dc.titleExtracción de información de documentos de identidad utilizando técnicas de aprendizaje de máquina
dc.typeTrabajo de grado - Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programMedellín - Minas - Maestría en Ingeniería - Analítica
dc.description.degreelevelMaestría
dc.description.degreenameMagíster en Ingeniería - Analítica
dc.identifier.instnameUniversidad Nacional de Colombia
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourlhttps://repositorio.unal.edu.co/
dc.publisher.departmentDepartamento de la Computación y la Decisión
dc.publisher.facultyFacultad de Minas
dc.publisher.placeMedellín
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellín
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.lembRedes neuronales (Computadoers)
dc.subject.proposalIentidad digital
dc.subject.proposalOCR
dc.subject.proposalDigital identity
dc.subject.proposalExtracción de información
dc.subject.proposalInformation extraction
dc.subject.proposalObject detection
dc.subject.proposalDetección de objetos
dc.title.translatedInformation extraction from identification documents using machine learning techniques
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dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
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dc.type.redcolhttp://purl.org/redcol/resource_type/TM
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dcterms.audience.professionaldevelopmentEstudiantes
dcterms.audience.professionaldevelopmentInvestigadores
dc.description.curricularareaÁrea Curricular de Ingeniería de Sistemas e Informática


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