Scattering materials are ubiquitous: from our skin and food, to everyday objects such as wax and soap, to industrial materials such as coatings and soft tissues. Common to all these materials is the complex way in which they interact with light. Their appearance is the result of photons that penetrate the material surface, and perform random walks inside the material before emerging towards a camera. Inverse scattering is, then, the problem of inverting this light transport process, in order to infer scattering parameters from images of a material. We approach inverse scattering as an appearance matching problem: given a set of measurements (images) of a material, we search for the scattering parameters which, when used to computationally render new images, minimize the difference with the captured ones. In full generality, this is a very challenging optimization problem, due to the high-dimensional search space and the non-linear dependence of images on scattering parameters. We present several contributions for making this optimization problem tractable. First, we introduce a computational framework for efficiently solving the appearance matching problem. Ourframework is based on a combination of operator theory, stochastic gradient descent, Monte Carlo rendering, and material dictionary representations. It allows inverting the light transport process in a broad range of scattering materials, without having to rely on common approximations such as single scattering and diffirsion. Additionally, it accommodates rich, high-dimensional material representations, enabling us to accurately measure parameters such as the scattering phase function shape, without having to rely on restrictive low-parameter models. To evaluate this framework, we created an acquisition setup that images thin material slabs under narrow-beam illumination from multiple lighting and viewing directions. Using measurements from this setup, we used our algorithm to infer the parameters of homogeneous scattering materials. Our experiments show that we can accurately recover all scattering parameters of ground-truth materials (reference polydispersions whose scattering parameters are given by Mie Theory). Additionally, using our measured scattering parameters for several common liquids and solids, we can accurately predict their appearance under novel geometric configurations. Second, we present a computational imaging system that allows capturing rich sets of measurements from scattering materials, to be used as the input in the appearance matching framework. Our system is based on interferometric techniques, and specifically on the optical coherence tomography framework. It collects measurements corresponding to decompositions of photon contributions into subsets, based on the distance they travelled inside the material, or their point of origin on the source illuminating the material, or both. These decompositions are equivalent to the measurements obtained from recently introduced computational photography techniques, such as transient imaging and spatial probing. However, our use of interferometry allows us to capture these decompositions at micron-scale resolutions, two to three orders of magnitude larger than previously possible. Such resolutions are necessary when collecting measurements for inverse scattering applications. We describe how to construct and optimize an optical assembbrfor this technique, and we build a prototype to measure and visualize scattering materials, as well as other optical phenomena. Third, we discuss ongoing work where we combine our computational framework and imaging system, in order to perform inverse scattering for more general, heterogeneous materials. We show how this combination can accommodate material representations tailored to very different types of heterogeneities, such as those present in skin, cloth, or jade. We discuss strategies for scaling up both the computational and imaging components of our methods, so that they can tackle the much higher-dimensionality of heterogeneous inverse scattering problems. Finally, we explore possible extensions towards measuring other material properties such as heterogeneous dispersion and birefringence.

A research project is underway to develop a gonio imager particularly dedicated to sample the Bidirectional Reflectance Distribution Function (BRDF) of materials and material compositions employed and created by multimaterial 3D printers. It comprises an almost colorimetric RGB camera and a spectrally tunable light source. In this paper, we investigate an important part of this system, particularly the approach to estimate reflectances from RGB values acquired under multiple illuminants. We first characterize the system by estimating the spectral sensitivities of the camera. Then, we use the sensitivities, a set of illuminants produced by the tunable light source and the corresponding sensor responses to estimate reflectances. For evaluating this approach, we measure the Neugebauer primary reflectances of a polyjet printer employing highly translucent photo-polymer printing materials colored in cyan, magenta, yellow and white. Spectral and colorimetric deviations to spectroradiometric comparison measurements (average 0.67 CIEDE2000 units / 0.0286 spectral RMS) are within the inter-instrument variability of hand-held spectrophotometers used in graphic arts for prints on paper.

Fast and reliable measurement of material appearance is crucial for many applications ranging from virtual prototyping to visual quality control. The most common appearance representation is BRDF capturing illumination- and viewing-dependent reflectance. One of the approaches to rapid BRDF measurement captures its subspace, using so called slices, by continuous movements of a light and camera in azimuthal directions, while their elevations remain fixed. This records set of slices in the BRDF space while remaining data are unknown. We present a novel approach to BRDF reconstruction based on a concept of anisotropic stencils interpolating values along predicted locations of anisotropic highlights. Our method marks an improvement over the original linear interpolation method, and thus we ascertain it to be a promising variant of interpolation from such sparse yet very effective measurements.

The 3D laser scanning technology has been reached by more and more users in the last years, thanks to a new market of low cost devices, more affordable for simple, non-professional use. The educational use is one of such environments, and its didactics purposes gives the opportunity to test new technology from a variety of different point of views. 3D laser scanning, for example, is very promising in environments like Design university education, where the control of the shape of an object is one of the topics discussed in courses, and one of the main focuses of the product design profession. This paper describes the use of this technology in students and research lab, and its metrological characterization, especially on the relationship between performances and object optical characteristics (like gloss and color), object position and ambient lighting. It is to keep in mind that, in a student lab, geometry reverse acquisition is one of the activities done to understand products layout: the knowledge of influences of surrounding and material characteristics on scanner performances is a key factor to improve the performance when low cost scanner are involved. The characterization performed gave the opportunity to students to test how such devices work, the output reliability, which are the inherent issues and what kind of strategies should be introduced to enhance the scanning quality, indeed one of the main problems of these low cost devices.

This article introduces a novel algorithm to learn optimal incident illumination for material classification using spectral bidirectional reflectance distribution function (BRDF) images. The method performs a joint selection of incident angle and spectral band in two steps: (1) clustering and selecting incident angles using statistics on the spectral BRDF images for a specific material, and (2) searching for the optimal angles and spectral bands that maximize material discriminability, which we measure in classification performance. The benefits of reducing the number of incident illumination angles include improving material classification, reducing computational time and storage, and allowing for a less cumbersome and potentially mobile imaging system. The authors show that their approach provides comparable material classification performance when using a reduced number of incident illuminations as compared with when using a larger number. They also compare their approach with prior work. © 2015 Society for Imaging Science and Technology.

We use a Fourier optics multispectral instrument to measure the BRDF of isotropic and anisotropic samples. The capacity to measure rapidly high angular BRDF patterns is useful to study complex BRDF behaviors in particular for anisotropic surfaces. Metallic two dimensional structured surfaces exhibit different diffusion properties along particular directions. Brushed metallic samples coated with transparent protective layer show complex BRDF patterns modulated by interference fringes due to the coating. The color of the surface is driven by the anisotropic diffusion and the coating thickness. The surface of OLED displays shows also complex scattering patterns due to the periodic pixel structure. We examine how to use spectral BRDF measurements to simulate the aspect of the surfaces and how to take into account the anisotropy in practice. Results are compared in some cases to aspect measurements made with multispectral imaging and punctual illumination source. Optical properties of curved OLED TV under parasitic illuminations are also presented.

Image based measurement techniques are increasingly used to perform multi-directional reflectance measurements of objects/materials. In these techniques, commercially available colour (RGB) cameras are used along with the monochrome CCD cameras to measure the radiance reflected from the object/material surface at multiple reflection directions. The data acquired through these cameras is used to estimate the BRDF of given sample/material. This paper presents an image-based method to measure the reflectance of the sample material using the camera spectral sensitivities. A multi-angle measurement setup described in previous studies was used to perform the measurements. A reflection model of the sample was derived in a colorimetric space using the Phong model. Camera spectral sensitivities were measured using a Bentham monochromator to build a tranformation from Camera RGB to CIEXYZ colour space. A reflection model was fitted in the colorimetric domain (CIEXYZ) for the sample materials used. Results show that image based multi-directional reflectance measurements can be performed using the camera spectral sensitivities.

There exists an increasing interest in reproducing surface appearances by means of digital printing, thereby expanding the reproduction from only color to reproduction of texture and reflection properties such as the BRDF. Previous research has focused on different ways to obtain control of the optical characteristics of digital prints, either by introducing additional inks or by modulating the surface texture on a macro level. The authors propose to utilize the different parameters of a printing system, which influence aspects such as the ink deposition and drying time, to impact the roughness of the print surface on a micro level. By investigating relationships between optical and geometric characteristics of printed surfaces, we study the hypothesis that both surface characteristics can be estimated from a single roughness parameter. From these findings, we propose a workflow to control reflection properties (including color) of a printed surface by determining ink coverage values and print parameters. © 2015 Society for Imaging Science and Technology.

Novel printing and layering technologies that incorporate a raised or embossed surface have demonstrated new opportunities for novel applications. Textured images have been used extensively in the print industry as decorative decals and embellishments to enhance the surface qualities of packaging and prints. As the resolution and print quality has improved, and the technology has become more accessible, there are now more opportunities to explore texture in artworks, especially in relation to tactile printing for blind or visually impaired. Over the last two decades, museums have broadened the idea of cultural accessibility for blind people, for example, to cultural events and museums. Access to knowledge began by enabling users to engage with texts and printed word, and then as second hand experience through audio books and description about artefacts and events, and now the opportunity to give access to images, such as artworks, picture books and photographs, in museums whereby a second hand experience is replaced by first hand experience. On a practical level, day-to-day understanding of identifying information and things, ways of identifying colour and colour relationships has been developed by Okudera (2015) in the form of textile tags to convey colour information is a practical method to enable blind people to identify the colour of their clothes and to know that their clothes colour co-ordinated. A simple iron on tactile tag, based on the hue circle, enabled users to identify colour relationships. Ten small raised (rubber to the touch) dots are arranged around a Munsell hue circle each representing primary colours, along with three raised vertical dots in the centre to represent white, grey and black. In order to identify the representative colour, a bigger dot or hole is punctured into the tag (Okudera). Tactile pictures for blind can provide an enhanced understanding for the user. Appropriate methods for image segmentation is necessary to distinguish different parts of a picture. Traditional approaches use contours and patterns, which creates a distinct and recognisable shape and enables separate objects to identified. A contour arises on the boundary between two surfaces and is usually described by a line. Different textures can also be incorporated to convey an idea of a picture. Living Paintings provide touch to see pictures, which can range from current events such as the Olympics to educational books such as dinosaurs to cultural object such as from the British Museum London. These relief tactile pictures use highly simplified shapes, but provide essential unambiguous information. The pages are vacuum formed using thermo plastic sheet over a carved or machined board, and then ring bound together with other pages to form a flip-book. This cheap method means that books can be mass-produced, widely circulated, and are fairly robust. However, we would argue that accuracy is not even wanted in most of the applications, as a certain degree of interpretation of the full body of things may be more valuable and welcome than a cold replica. An interesting project, where interpretation and exploration is fundamental, is demonstrated by Studios Durero. The Didu project in collaboration with the Prado Madrid, has attempted to make classic paintings accessible to visually impaired people through relief prints. Their designers worked alongside art specialists and with visually impaired people to understand how to either exaggerate textures already present in a painting, or to create new ones that would be visually relevant but needed to be exaggerated to be perceived by blind participants. Likewise 3D Photoworks have studied how to make fine art prints accessible by building a high-relief surface of paintings, and Tooteko use sound and touch to assist the user to explore a range of images. This short presentation will discuss aspects and requirements of relief, tactile 2.5D printing, and surface manufacturing in relation to tactile printing for the visually impaired.