Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall, Upper Saddle River (2008)
Papari, G., Petkov, N.: Edge and line oriented contour detection: state of the art. Image Vis. Comput. 29, 79–103 (2011)
Sánchez-González, M., Cabrera, M., Herrera, P.J., Vallejo, R., Cañellas, I., Montes, F.: Basal area and diameter distribution estimation using stereoscopic hemispherical images. Photogram. Eng. Remote Sens. 82(8), 605–616 (2016)
Roman-Rangel, E., Pallan, C., Odobez, J.M., Gatica-Perez, D.: Analyzing ancient maya glyph collections with contextual shape descriptors. Int. J. Comput. Vis. 94(1), 101–117 (2011)
Roman-Rangel, E., Marchand-Maillet, S.: Shape-based detection of Maya hieroglyphs using weighted bag representations. Pattern Recogn. 48(4), 1161–1173 (2015)
Herrera, P.J., Pajares, G., Guijarro, M., Ruz, J.J., Cruz, J.M., Montes, F.: A featured-based strategy for stereovision matching in sensors with fish-eye lenses for forest environments. Sensors 9(12), 9468–9492 (2009)
Herrera, P.J., Dorado, J., Ribeiro, A.: A novel approach for weed type classification based on shape descriptors and a fuzzy decision-making method. Sensors 14, 15304–15324 (2014)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)
Smith, S.M., Brady, J.M.: SUSAN - a new approach to low level image processing. Int. J. Comput. Vis. 23(1), 45–78 (1997)
Ballard, D.H.: Generalizing the hough transform to detect arbitrary shapes. Pattern Recogn. 13(2), 111–122 (1981)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: 5th European Conference on Computer Vision, pp. 484–498. Springer, UK (1998)
Zhang, K., Zhang, L., Song, H., Zhou, W.: Active contours with selective local or global segmentation: a new formulation and level set method. Image Vis. Comput. 28(4), 668–676 (2010)
Duque-Domingo, J.: Aplicación para reconocimiento visual y datación de jeroglíficos egipcios. Máster Universitario en Investigación en Ingeniería del Software y Sistemas Informáticos, UNED. Final Master Project (2014)
El-Zaart, A.: Images thresholding using ISODATA technique with gamma distribution. Pattern Recogn. Image Anal. 20(1), 29–41 (2010)
Gonzales-Barron, U., Butler, F.: A comparison of seven thresholding techniques with the k-means clustering algorithm for measurement of bread-crumb features by digital image analysis. J. Food Eng. 74, 268–278 (2006)
Macedo-Cruz, A., Pajares, G., Santos, M., Villegas-Romero, I.: Digital image sensor-based assessment of the status of oat (Avena sativa L.) crops after frost damage. Sensors 11, 6015–6036 (2011)
Jiménez, C.: Modelos simbólico-conexionistas para la segmentación y descripción de Marcas de Cantero. Máster Universitario en Investigación en Ingeniería de Software y Sistemas Informáticos, UNED. Final Master Project (2014)
Duque-Domingo, J., Cerrada, C., Valero, E., Cerrada, J.A.: Indoor positioning system using depth maps and wireless networks. J. Sens. 2016, 1–8 (2016)
Acknowledgements
This work has been developed with the help of the research projects DPI2013-44776-R and DPI2016-77677-P of the MICINN. It also belongs to the activities carried out within the framework of the research network CAM Robo-City2030 S2013/MIT-2748 of the Comunidad de Madrid.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-70836-2_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70835-5
Online ISBN: 978-3-319-70836-2
eBook Packages: EngineeringEngineering (R0)