Publicación: A vision-based strategy to segment and localize ancient symbols written in stone
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2017-12-21
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info:eu-repo/semantics/openAccess
Licencia Creative Commons
http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
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Springer
Resumen
This work proposes an automatic method to detect ancient symbols written in stone. The proposed method takes into account well-known techniques used in computer vision to identify the contour of the symbols in the image. The two-stage method consists of segmentation and localization processes. Segmentation process includes a pre-processing step, edge detection and thresholding. Localization process is based on two conditions that take into account several parameters, like the distance between points, and the orientation and the continuity of the edges. This proposal has been applied to localize Egyptian cartouches (borders enclosing the name of a king) and stonemason’s marks from images obtained under varying lighting conditions (controlled and natural lighting). The proposed method is compared favorably against other methods based on chain coding, neural networks and statistical correlation. The promising results give new possibilities to identify and recognize complex symbols and ancient texts.
Descripción
Esta es la versión aceptada del artículo. La versión registrada fue publicada por primera vez en ROBOT 2017: Third Iberian Robotics Conference, vol 694, está disponible en línea como capítulo de libro en el sitio web del editor: Springer dentro de su serie "Advances in Intelligent Systems and Computing" : https://doi.org/10.1007/978-3-319-70836-2_21.
This is the accepted version of the article. The registered version was published for the first time in ROBOT 2017: Third Iberian Robotics Conference, vol 694, and is available online as a book chapter on the publisher's website: Springer in its series 'Advances in Intelligent Systems and Computing': https://doi.org/10.1007/978-3-319-70836-2_21.
Categorías UNESCO
Palabras clave
Image segmentation, edge detection, object localization
Citación
Duque-Domingo, J., Herrera, P.J., Cerrada, C., Cerrada, J.A. (2018). A Vision-Based Strategy to Segment and Localize Ancient Symbols Written in Stone. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_21
Centro
E.T.S. de Ingeniería Informática
Departamento
Ingeniería de Software y Sistemas Informáticos