37 research outputs found
Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon
In a study of multispectral and hyperspectral reflectance imaging, a Round Robin Test assessed the performance of different systems for the spectral digitisation of artworks. A Russian icon, mass-produced in Moscow in 1899, was digitised by ten institutions around Europe. The image quality was assessed by observers, and the reflectance spectra at selected points were reconstructed to characterise the icon’s colourants and to obtain a quantitative estimate of accuracy. The differing spatial resolutions of the systems affected their ability to resolve fine details in the printed pattern. There was a surprisingly wide variation in the quality of imagery, caused by unwanted reflections from both glossy painted and metallic gold areas of the icon’s surface. Specular reflection also degraded the accuracy of the reconstructed reflectance spectrum in some places, indicating the importance of control over the illumination geometry. Some devices that gave excellent results for matte colour charts proved to have poor performance for this demanding test object. There is a need for adoption of standards for digitising cultural heritage objects to achieve greater consistency of system performance and image quality.This article arose out of a Short-Term Scientific Mission (STSM) conducted by Tatiana Vitorino when visiting University College London during a 2-week period in late October 2015. The research was carried out under the auspices of the European COST Action TD1201 Colour and Space in Cultural Heritage (COSCH). The project website is at http://www.cosch.info. Under the COST rules, TV received funding for travel and accommodation expenses, and all coauthors were able to claim travel expenses to attend the subsequent COSCH project meeting. No other funding was received from COSCH for labour or equipment and all work was done on a voluntary pro bono basis.info:eu-repo/semantics/publishedVersio
KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS
Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In
practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of
modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being
accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and
their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human
interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of
algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing
steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the
advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for
applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our
approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language
(SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’
knowledge of the scene and algorithmic processing
Ein Verfahren zur Herstellung digitaler Hoehenmodelle aus photogrammetrischen Stereomodellen mit Hilfe der flaechenhaften Korrelation in digitalen Bildern
SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman