Computer Algorithm for Archaeological Projectile Points Automatic Classification
| Autor: | Fernando Flores, Francisco García Ugalde, Maria del Pilar Angeles, Alfonso Gastelum Strozzi, Mariko Nakano Miyatake, José Luis Punzo Díaz, Jesús Zarco Navarro |
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| Rok vydání: | 2019 |
| Předmět: |
010506 paleontology
060102 archaeology Computer science Orientation (computer vision) Projectile point ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Context (language use) 06 humanities and the arts Conservation 01 natural sciences Computer Graphics and Computer-Aided Design Archaeology Computer Science Applications Support vector machine Digital image Computer Science::Computer Vision and Pattern Recognition Histogram 0601 history and archaeology Shape context Pyramid (image processing) 0105 earth and related environmental sciences Information Systems |
| Zdroj: | Journal on Computing and Cultural Heritage. 12:1-30 |
| ISSN: | 1556-4711 1556-4673 |
| DOI: | 10.1145/3300972 |
| Popis: | The manual archaeological projectile point morphological classification is an extensive and complex process since it involves a large number of categories. This article presents an algorithm that automatically makes this process, based on the projectile point digital image and using a classification scheme according to global archaeological approaches. The algorithm supports different conditions such as changes in scale and quality of the image. Moreover, it requires only a uniform background and an approximate north--south projectile point orientation. The principal computer methods that compose the algorithm are the curvature scale space map (CSS-map), the gradient contour on the projectile point, and the support vector machines (SVM) algorithm. Finally, the classifier was trained and tested on a dataset of approximately 800 projectile points images, and the results have shown a better performance than other shape descriptors such as Pyramid of Histograms of Orientation Gradients (PHOG), Histogram of Orientation Shape Context (HOOSC) (both used in a bag-of-words context), and geometric moment invariants (Hu moments). |
| Databáze: | OpenAIRE |
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