Objective: To demonstrate optical coherence tomography for high-resolution, noninvasive imaging of the human retina. Optical coherence tomography is a new imaging technique analogous to ultrasound B scan that can provide cross-sectional images of the retina with micrometer-scale resolution. Design: Survey optical coherence tomographic examination of the retina, including the macula and optic nerve head in normal human subjects. Settings Research laboratory. Participants: Convenience sample of normal human subjects. Main Outcome Measures: Correlation of optical coherence retinal tomographs with known normal retinal anatomy. Results: Optical coherence tomographs can discriminate the cross-sectional morphologic features of the fovea and optic disc, the layered structure of the retina, and normal anatomic variations in retinal and retinal nerve fiber layer thicknesses with 10- μm depth resolution. Conclusion: Optical coherence tomography is a potentially useful technique for high depth resolution, cross-sectional examination of the fundus.

Optical Coherence Tomography of the Human Retina

Virtual reality: applications and implications for tourism.

Recent developments in techniques for modeling, digitizing and visualizing 3D shapes has led to an explosion in the number of available 3D models on the Internet and in domain-specific databases. This has led to the development of 3D shape retrieval systems that, given a query object, retrieve similar 3D objects. For visualization, 3D shapes are often represented as a surface, in particular polygonal meshes, for example in VRML format. Often these models contain holes, intersecting polygons, are not manifold, and do not enclose a volume unambiguously. On the contrary, 3D volume models, such as solid models produced by CAD systems, or voxels models, enclose a volume properly. This paper surveys the literature on methods for content based 3D retrieval, taking into account the applicability to surface models as well as to volume models. The methods are evaluated with respect to several requirements of content based 3D shape retrieval, such as: (1) shape representation requirements, (2) properties of dissimilarity measures, (3) efficiency, (4) discrimination abilities, (5) ability to perform partial matching, (6) robustness, and (7) necessity of pose normalization. Finally, the advantages and limitations of the several approaches in content based 3D shape retrieval are discussed.

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A survey of content based 3D shape retrieval methods

The importance of landscape and heritage recording and documentation with optical remote sensing sensors is well recognized at international level. The continuous development of new sensors, data capture methodologies and multi-resolution 3D representations, contributes significantly to the digital 3D documentation, mapping, conservation and representation of landscapes and heritages and to the growth of research in this field. This article reviews the actual optical 3D measurement sensors and 3D modeling techniques, with their limitations and potentialities, requirements and specifications. Examples of 3D surveying and modeling of heritage sites and objects are also shown throughout the paper.

https://www.mdpi.com/2072-4292/3/6/1104/pdf

Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning

A Survey of Content Based 3D Shape Retrieval Methods (Figure 5).

Spectral imaging technology, widely used in remote sensing applications, such as satellite or radar imaging, has recently gained importance in the field of artwork conservation. In particular, multispectral imaging in the near-infrared region (NIR) has proved useful in analyzing ancient paintings because of the transparency of most pigments and their varied reflectance changes over this spectral region. A variety of systems, with different detectors and filtering or dispersing technologies, have been implemented. Despite the recognized potential of multispectral NIR imaging, which provides information on both spectral and spatial domains (thus extending the capabilities of conventional imaging and spectroscopy), most of the systems currently used in art diagnostics have limitations. The technology is still in its early stages of development in this field. In this Account, we present the scanning multispectral IR reflectography (SMIRR) technique for artwork analysis, together with an integrated device for ...

Scanning multispectral IR reflectography SMIRR: an advanced tool for art diagnostics.

Three-dimensional modelling of statues: the Minerva of Arezzo

Infrared reflectography is a well-known technique based on wideband imaging in the near-infrared (NIR) range used for painting diagnostics in conservation laboratories.. This work is focused on the application of multiband reflectography for analysis of pictorial layers and differentiated detection of painting features. This technique generates a set of narrowband NIR images of the painting. Starting from a dataset that is registered, metrically correct, and calibrated, the capability of collecting both spectral and spatial information has been exploited by processing the image cube with interplane techniques. Examples on artworks by Caravaggio, Veronese, Bronzino, and Schiavone are presented.

Multispectral Infrared Reflectography to Differentiate Features in Paintings

Multispectral imaging of paintings by optical scanning

We present a scanning device for multispectral imaging of paintings in the 380–2300 nm spectral range (32 VIS+14 NIR bands). The system is based on contact-less and single-point measurement of the spectral reflectance factor. Multispectral images are obtained by scanning the painted surface under investigation. At present the VIS and NIR modules work separately due to the lack of synchronization between them. Measurement campaigns were carried out on several paintings in situ and at the INOA Optical Metrology Laboratory located inside the Opificio delle Pietre Dure in Florence. We report herein on the measurements carried out on a few panel and canvas paintings. Multivariate image analyses (MIAs) were performed and the detected images were analysed by means of the conventional principal component analysis (PCA) and the K-nearest-neighbouring cluster analysis (KNN).

http://iopscience.iop.org/article/10.1088/1464-4258/10/6/064011/pdf

Raffaella Fontana

Papers

Scanning multispectral IR reflectography SMIRR: an advanced tool for art diagnostics.

Three-dimensional modelling of statues: the Minerva of Arezzo

Multispectral Infrared Reflectography to Differentiate Features in Paintings

Multispectral imaging of paintings by optical scanning

A scanning device for VIS–NIR multispectral imaging of paintings