Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/136194
Título: A survey of handwriting synthesis from 2019 to 2024: A comprehensive review
Autores/as: Díaz Cabrera, Moisés 
Mendoza García, Andrea
Ferrer Ballester, Miguel Ángel 
Sabourin, Robert
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Generation
Handwriting
Offline
Online
Review, et al.
Fecha de publicación: 2025
Publicación seriada: Pattern Recognition 
Resumen: Handwriting, as a uniquely human skill, contributes to fine motor development and cognitive growth. Beyond mere functionality, handwriting carries individuality and subtle emotional nuances, evoking feelings of intimacy and authenticity. Consequently, the generation of synthetic handwritten manuscripts should not only prioritize the production of legible text, but also seek to enhance personalization and authenticity in digital communication. This enhancement renders handwriting synthesis invaluable in domains such as digital marketing and e-learning. Notably, handwriting synthesis plays a pivotal role in forensic science, particularly in signature verification, to bolster security and prevent fraud. Additionally, it has the potential to enhance accessibility, particularly for individuals with disabilities, and assist in health monitoring among elderly populations. Motivated by the significance of handwriting synthesis, this paper conducts a comprehensive literature review on the synthetic generation of handwriting and signatures. By examining research from 2019 to 2024, we categorize methods of synthesis, evaluate synthetic handwriting quality, and explore practical applications. Furthermore, we provide insights into publicly available code resources and emerging synthetic databases.
URI: http://hdl.handle.net/10553/136194
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2025.111357
Fuente: Pattern Recognition [ISSN 0031-3203], v. 162, (Junio 2025)
Colección:Artículos
Adobe PDF (3,87 MB)
Vista completa

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.