Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/107470
Title: Writing Order Recovery in Complex and Long Static Handwriting
Authors: Díaz Cabrera, Moisés 
Crispo, Gioele
Parziale, Antonio
Marcelli, Angelo
Ferrer Ballester, Miguel Ángel 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Cluster Resolution
Complex and Long Handwriting
Good Continuity Criteria
Writing Order Recovery
Issue Date: 2021
Project: Generacion de Un Marco Unificado Para El Desarrollo de Patrones Biometricos de Comportamiento 
Modelado cinemático 3D para la caracterización del movimiento humano, animal y robótico 
Journal: International Journal Of Interactive Multimedia And Artificial Intelligence 
Abstract: The order in which the trajectory is executed is a powerful source of information for recognizers. However, there is still no general approach for recovering the trajectory of complex and long handwriting from static images. Complex specimens can result in multiple pen-downs and in a high number of trajectory crossings yielding agglomerations of pixels (also known as clusters). While the scientific literature describes a wide range of approaches for recovering the writing order in handwriting, these approaches nevertheless lack a common evaluation metric. In this paper, we introduce a new system to estimate the order recovery of thinned static trajectories, which allows to effectively resolve the clusters and select the order of the executed pendowns. We evaluate how knowing the starting points of the pen-downs affects the quality of the recovered writing. Once the stability and sensitivity of the system is analyzed, we describe a series of experiments with three publicly available databases, showing competitive results in all cases. We expect the proposed system, whose code is made publicly available to the research community, to reduce potential confusion when the order of complex trajectories are recovered, and this will in turn make the trajectories recovered to be viable for further applications, such as velocity estimation.
URI: http://hdl.handle.net/10553/107470
ISSN: 1989-1660
DOI: 10.9781/ijimai.2021.04.003
Source: International Journal Of Interactive Multimedia And Artificial Intelligence [1989-1660],
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