Simple and effective method for measuring translucency using edge loss: optimization of measurement conditions and applications for skin

Yoshida, Kenichiro; Komeda, Nobutoshi; Ojima, Nobutoshi; Iwata, Kayoko

doi:10.1117/1.3646208

Cited by 13 publications

(12 citation statements)

References 22 publications

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“…Vertical light transport is measured in transmission mode for which the 4 mm-thick sample is placed between light source and detector. Lateral light transport is measured in reflectance mode (detector and light source are on the same side of the sample in a 45/0 geometry) employing the spectral edge-loss difference [Yoshida et al 2011], which requires two spectral measurements both with the same detection area (circular with 2mm diameter) but with two different illuminating areas. This is achieved by using two circular apertures: one with 2mm and one with 8mm diameter.…”

Section: Color and Translucency Management 51 Measurementsmentioning

confidence: 99%

3D printing spatially varying color and translucency

et al. 2018

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Fig. 1. Design control and perceptual reproduction of material translucency for full color 3D printing: (a) a printed anatomy model with opaque and translucent parts, revealing internal structures; (b) a polished transparent Lion with a red mane and 3D logo inside; (c) a transparent lizard with colored scales illuminated from below by a checkerboard pattern; (d) a close-up (see Figure 12 for the full view) of wax and a 3D print reproducing the wax's translucent appearance.We present an efficient and scalable pipeline for fabricating full-colored objects with spatially-varying translucency from practical and accessible input data via multi-material 3D printing. Observing that the costs associated with BSSRDF measurement and processing are high, the range of 3D printable BSSRDFs are severely limited, and that the human visual system relies only on simple high-level cues to perceive translucency, we propose a method based on reproducing perceptual translucency cues. The input to our pipeline is an RGBA signal defined on the surface of an object, making our approach accessible and practical for designers. We propose a framework for extending standard color management and profiling to combined color and translucency management using a gamut correspondence strategy we call opaque relative processing. We present an efficient streaming method to compute voxel-level material arrangements, achieving both realistic reproduction of measured translucent materials and artistic effects involving multiple fully or partially transparent geometries.

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Section: Color and Translucency Management 51 Measurementsmentioning

confidence: 99%

3D printing spatially varying color and translucency

et al. 2018

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“…To specify lateral light transport we propose to use the spectrophotometric edge-loss di erence ∆L 0,1 = |L * 0 − L * 1 |, where L * 0 and L * 1 are lightness values obtained from re ectance measurements of the same sample employing two di erent measurement conditions (Yoshida et al 2011). A measurement condition is characterized by the ratio a = a d /a i , where a d is the diameter of a circular detection area and a i is the diameter of a circular illuminated area used by the spectrophotometer.…”

Section: Measuring Lateral and Vertical Light Transportmentioning

confidence: 99%

“…Note that spectrophotometric measurements are always relative to a reference measurement and factors such as the sensor's quantum e ciency or the light source's Spectral Power Distribution (SPD) are canceled out. More details including a derivation of the measurement equations from BSSRDFs is given by Yoshida et al (2011). We measure vertical light transport using a transmission setup, where the material is placed between detector and illumination (see Figure 2 right).…”

Section: Measuring Lateral and Vertical Light Transportmentioning

confidence: 99%

Redefining A in RGBA: Towards a Standard for Graphical 3D Printing

Urban,

Tanksale,

Brunton

et al. 2017

Preprint

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Advances in multimaterial 3D printing have the potential to reproduce various visual appearance a ributes of an object in addition to its shape. Since many existing 3D le formats encode color and translucency by RGBA textures mapped to 3D shapes, RGBA information is particularly important for practical applications. In contrast to color (encoded by RGB), which is specied by the object's re ectance, selected viewing conditions and a standard observer, translucency (encoded by A) is neither linked to any measurable physical nor perceptual quantity. us, reproducing translucency encoded by A is open for interpretation.In this paper, we propose a rigorous de nition for A suitable for use in graphical 3D printing, which is independent of the 3D printing hardware and so ware, and which links both optical material properties and perceptual uniformity for human observers. By deriving our de nition from the absorption and sca ering coe cients of virtual homogenous reference materials with an isotropic phase function, we achieve two important properties. First, a simple adjustment of A is possible, which preserves the translucency appearance if an object is rescaled for printing. Second, determining the value of A for a real (potentially non-homogenous) material, can be achieved by minimizing a distance function between light transport measurements of this material and simulated measurements of the reference materials. Such measurements can be conducted by commercial spectrophotometers used in graphic arts.Finally, we conduct visual experiments employing the method of constant stimuli, and derive from them an embedding of A into a nearly perceptuallyuniform scale of translucency for the reference materials.

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“…5,9 Yet, there seem to be differences in the range of colour leading to increased transparency, as pinpointed by Nishimuta et al 10 Several works have attempted to identify skin parameters important for transparency. 1,5,[11][12][13][14] Overall, they show that colour, colour homogeneity, texture and light reflection are important. Nevertheless, in almost all these studies, skin characteristics were acquired using an entire range of different devices and techniques: spectrophotometer, goniometer, Corneometer ® , confocal microscope, skin replicas, etc., and almost exclusively focussed on the cheek.…”

Section: Introductionmentioning

confidence: 96%

“…Several works have attempted to identify skin parameters important for transparency 1,5,11–14 . Overall, they show that colour, colour homogeneity, texture and light reflection are important.…”

Section: Introductionmentioning

confidence: 99%

Analysis of correlation and construction of a predictive model of skin transparency using parameters from digital images of the face

Marin¹,

Honda²,

Nakajima³

et al. 2022

Skin Research and Technology

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Background Skin transparency is a cosmetic asset highly considered by Asian women. Resulting from complex light interactions within the skin, but still not fully understood, there is no simple method to measure it objectively. In this study, skin parameters from digital images were analysed to build a model predicting transparency. Materials and methods Initially, 71 Japanese women (between ages 50 and 60 years) were recruited. This group was then extended to 262 women (between ages 21 and 60 years). Pictures of their faces were taken with the Colorface® under diffuse light and different polarisation angles. Experts graded their transparency using pictures. Pictures were also used to compute 958 skin colour and surface parameters from different regions of the face. Results In the initial group of 71 subjects, 109 parameters correlated with transparency. Half of them are from the cheek and relate to colour or colour homogeneity. If the cheek presented the largest proportion of correlated parameters, best correlations were usually found in other facial regions. Multiple regressions from some cheek parameters can predict up to 80% of transparency. Stepwise regression on parameters from 262 subjects led to a six‐parameter model, which is highly correlated (R = 84.1%) with transparency. It combines skin texture, colour, colour homogeneity and gloss parameters. If half of them are from the cheek, the others are from the tear trough, the full face and the cheekbone. Conclusion Using parameters from digital pictures exclusively, we propose a model that accurately reflects transparency. Including parameters previously shown to relate to transparency, this model should be useful for future dermatology and cosmetic research.

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Simple and effective method for measuring translucency using edge loss: optimization of measurement conditions and applications for skin

Cited by 13 publications

References 22 publications

3D printing spatially varying color and translucency

3D printing spatially varying color and translucency

Redefining A in RGBA: Towards a Standard for Graphical 3D Printing

Analysis of correlation and construction of a predictive model of skin transparency using parameters from digital images of the face

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