Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR

Automatic information extraction from identity documents remains a challenging task due to variations in image quality, document layout, and text appearance. This study proposes a key information extraction system for the Peruvian National Identity Document (DNI) by integrating object detection and...

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Autor principal: Quispe Valero, Jhoselyn Noemi
Otros Autores: Huanca Torres, Fredy Abel
Formato: Tesis de pregrado
Lenguaje:inglés
Publicado: Universidad Peruana Unión 2026
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author Quispe Valero, Jhoselyn Noemi
author2 Huanca Torres, Fredy Abel
author_browse Huanca Torres, Fredy Abel
Quispe Valero, Jhoselyn Noemi
author_facet Huanca Torres, Fredy Abel
Quispe Valero, Jhoselyn Noemi
author_sort Quispe Valero, Jhoselyn Noemi
collection Repositorio institucional
description Automatic information extraction from identity documents remains a challenging task due to variations in image quality, document layout, and text appearance. This study proposes a key information extraction system for the Peruvian National Identity Document (DNI) by integrating object detection and Transformer-based text inference into a unified processing pipeline. The proposed approach combines YOLO11 for the detection and segmentation of regions of interest (ROI) and TrOCR for inferring the textual content of each identified field. The system was trained and evaluated using multiple document fields, including document number, given names, surnames, date of birth, and sex. Experimental results indicate consistent performance in both detection and text inference tasks, even without incorporating explicit preprocessing or post-processing stages. In particular, the fine-tuning process applied to TrOCR improved the recognition of compound names and Spanish-specific characters, including accented vowels and the letter ñ. The achieved performance was comparable to and, in some cases, surpassed that reported in related studies under equivalent evaluation metrics. Furthermore, the proposed methodology was integrated into a functional web-based application, enabling validation of the complete extraction workflow and the structured organization of the inferred information. Overall, the findings support the feasibility of the proposed system for automatic information extraction from identity documents under real-world conditions.
escuela_str_mv Escuela Profesional de Ingeniería de Sistemas
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linea_str_mv Gestión de TI
ocde_area_str_mv Ciencias naturales
ocde_disciplina_str_mv Computación y ciencias de la información
ocde_str_mv 1.02.01
programa_nombre_str_mv INGENIERÍA DE SISTEMAS
programa_pxx_str_mv P27
programa_uri_str_mv http://upeu.edu.pe/sys/programas/programa/ingenieria-de-sistemas
publishDate 2026
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spelling Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR Quispe Valero, Jhoselyn Noemi Huanca Torres, Fredy Abel Information extraction Identity document processing Region of interest Object detection Text inference Transformer-based models Automatic information extraction from identity documents remains a challenging task due to variations in image quality, document layout, and text appearance. This study proposes a key information extraction system for the Peruvian National Identity Document (DNI) by integrating object detection and Transformer-based text inference into a unified processing pipeline. The proposed approach combines YOLO11 for the detection and segmentation of regions of interest (ROI) and TrOCR for inferring the textual content of each identified field. The system was trained and evaluated using multiple document fields, including document number, given names, surnames, date of birth, and sex. Experimental results indicate consistent performance in both detection and text inference tasks, even without incorporating explicit preprocessing or post-processing stages. In particular, the fine-tuning process applied to TrOCR improved the recognition of compound names and Spanish-specific characters, including accented vowels and the letter ñ. The achieved performance was comparable to and, in some cases, surpassed that reported in related studies under equivalent evaluation metrics. Furthermore, the proposed methodology was integrated into a functional web-based application, enabling validation of the complete extraction workflow and the structured organization of the inferred information. Overall, the findings support the feasibility of the proposed system for automatic information extraction from identity documents under real-world conditions. 2026-08-11 2026-08-31T17:40:55Z 2028-08-11 info:eu-repo/date/embargoEnd/2028-08-11 info:eu-repo/semantics/bachelorThesis https://hdl.handle.net/20.500.12840/10609 eng info:eu-repo/semantics/embargoedAccess https://creativecommons.org/licenses/by-nc/4.0/ application/pdf Universidad Peruana Unión PE oai:repositorio.upeu.edu.pe:20.500.12840/10609 2026-11-10T17:45:09Z
spellingShingle Information extraction
Identity document processing
Region of interest
Object detection
Text inference
Transformer-based models
Quispe Valero, Jhoselyn Noemi
Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title_full Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title_fullStr Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title_full_unstemmed Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title_short Modelo de extracción de información clave para el Documento Nacional de Identidad Peruano mediante YOLO y TrOCR
title_sort modelo de extraccion de informacion clave para el documento nacional de identidad peruano mediante yolo y trocr
topic Information extraction
Identity document processing
Region of interest
Object detection
Text inference
Transformer-based models
topic_facet Information extraction
Identity document processing
Region of interest
Object detection
Text inference
Transformer-based models
url https://hdl.handle.net/20.500.12840/10609
work_keys_str_mv AT quispevalerojhoselynnoemi modelodeextracciondeinformacionclaveparaeldocumentonacionaldeidentidadperuanomedianteyoloytrocr