5 resultados para Sparkle
em Universidad de Alicante
Resumo:
For suitable illumination and observation conditions, sparkles may be observed in metallic coatings. The visibility of these sparkles depends critically on their intensity, and on the paint medium surrounding the metallic flakes. Based on previous perception studies from other disciplines, we derive equations for the threshold for sparkles to be visible. The resulting equations show how the visibility of sparkles varies with the luminosity and distance of the light source, the diameter of the metallic flakes, and the reflection properties of the paint medium. The predictions are confirmed by common observations on metallic sparkle. For example, under appropriate conditions even metallic flakes as small as 1 μm diameter may be visible as sparkle, whereas under intense spot light the finer grades of metallic coatings do not show sparkle. We show that in direct sunlight, dark coarse metallic coatings show sparkles that are brighter than the brightest stars and planets in the night sky. Finally, we give equations to predict the number of visually distinguishable flake intensities, depending on local conditions. These equations are confirmed by previous results. Several practical examples for applying the equations derived in this article are provided.
Resumo:
Materials with new visual appearances have emerged over the last few years. In the automotive industry in particular there is a growing interest in materials with new effect finishes, such as metallic, pearlescent, sparkle, and graininess effects. Typically, for solid colours the mean of three measurements with repetitions is sufficient to obtain a representative measurement for colour characterisation. However, gonio-apparent panels have non-homogeneous colours, and there are no studies that recommend the minimum number of repetitions for colour, sparkle, and graininess characterisation of this type of panel. We assume that colour panels incorporating special-effect pigments in their colour recipes will require a higher minimum number of measurements than solid colour panels. Therefore, the purpose of this study is to verify this assumption by using a multiangle BYK-mac spectrophotometer, given that it is currently the only commercial device that can measure colour, sparkle, and graininess values simultaneously. In addition, a possible methodology is given for establishing the minimum number of measurements when characterising gonio-apparent materials using a specific instrument, able to be implemented in future instruments when determining multiple appearance attributes (colour, gloss, sparkle, etc.) for many coloration technologies. Thus, we studied the minimum number of measurements needed to characterise the colour, sparkle, and graininess of three types of sample with solid, metallic, and pearlescent coatings respectively. Twenty measurements were made at twenty random positions (different target areas) of 90 samples. The minimum number of measurements for all these variables was determined on the basis of the point at which the cumulative mean value became constant. Thus, applying new statistical tools, it is clearly shown that metallic and pearlescent panels require more colour measurements than solid panels, in particular when geometries are being measured in a specular direction. As regards texture (sparkle and graininess), more measurements are needed for graininess than for sparkle, and more for metallic panels than for pearlescent panels.
Resumo:
Clase invitada impartida en marzo 2011 en la asignatura "Colour on industry" del máster Erasmus Mundus "Color in Informaticas and Media Technology" en la Universidad de Granada.
Resumo:
Charla realizada en el pasado 1st BYK-Gardner Iberian Automotive Meeting, celebrado en Alicante, entre los días 13 y 14 de Octubre de 2011: http://web.csidiomas.ua.es/congresos/iberianautomotive/index.html
Resumo:
New color-measuring instruments known as multiangle spectrophotometers have been recently created to measure and characterize the goniochromism of special-effect pigments in many materials with a particular visual appearance (metallic, interference, pearlescent, sparkle, or glitter). These devices measure the gonioapparent color from the spectral relative reflectance factor and the L*a*b* values of the sample with different illumination and observation angles. These angles usually coincide with requirements marked in American Society for Testing and Materials (ASTM) and Deutsches Institut Für Normung standards relating to the gonioapparent color, but the results of comparisons between these instruments are still inconclusive. Therefore, the main purpose of this study is to compare several multiangle spectrophotometers at a reproducibility level according to ASTM E2214-08 guidelines. In particular, we compared two X-Rite multi-gonio spectrophotometers (MA98 and MA68II), a Datacolor multi-gonio spectrophotometer (FX10), and a BYK multi-gonio spectrophotometer (BYK-mac). These instruments share only five common measurement geometries: 45° × −30° (as 15°), 45° × −20° (as 25°), 45° × 0° (as 45°), 45° × 30° (as 75°), 45° × 65° (as 110°). Specific statistical studies were used for the reproducibility comparison, including a Hotelling test and a statistical intercomparison test to determine the confidence interval of the partial color differences ΔL*, Δa*, Δb*, and the total color difference ΔE*ab. This was conducted using a database collection of 88 metallic and pearlescent samples that were measured 20 times without the replacement of all the instruments. The final findings show that in most measurement geometries, the reproducibility differences between pairs of instruments are statistically significant, although in general, there is a better reproducibility level at certain common geometries for newer instruments (MA98 and BYK-mac). This means that these differences are due to systematic or bias errors (angle tolerances for each geometry, photometric scales, white standards, etc.), but not exclusively to random errors. However, neither of the statistical tests used is valid to discriminate and quantify the detected bias errors in this comparison between instruments.