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New pioneering technology to objectively evaluate total perception of structured surfaces

Our visual perception is influenced by color, gloss and the surface structure. Our visual rating takes all three parameters into consideration and makes an overall judgement. Up to now, grain or surface structure could only be judged visually or with high sophisticated microscopes. This has changed with the new spectro2profiler, a pioneering technology combining color, gloss, 2D reflectivity and 3D topography in a robust, portable tool with a short measuring time.

spectro2profiler - objektive evaluation of textured surfaces

Table of Contents

  1. Introduction - Color analysis is not enough

  2. 3D Topography analysis using photometric stereo technique

  3. Watershed analysis to define structure cell sizes

  4. Conventional measurement of reflectivity and gloss

  5. Spatially resolved 2D reflectivity measurement

  6. Combination of 3D topography data with 2D reflectivity data

  7. A practical example as found in the automotive industry

  8. Conclusion

  9. References

Introduction - Color analysis is not enough

Uniform appearance is a crucial quality criterion for many products. The choice of material and production process variations influence the surface quality, for example the cell size of powder coatings is highly dependent on paint film thickness and curing conditions. Another example are injection molding applications where fluctuations in tool pressure and temperature will show up in gloss and contrast variations. With the change of just one material or process parameter, the visual perception of color and appearance can be changed significantly. So far visual assessment was the only way to deliver a complete judgement of a textured surface including color and gloss evaluation. The recent developments of color and gloss meters significantly improved quality control, but do not include the effects of structure or complex gloss behavior of 3D-surfaces. Therefore, 3D microscopes are used to provide very detailed information of the surface structure in the laboratory for research purposes, but not suitable for fast and easy analysis of production quality.

3D Topography analysis using photometric stereo technique

Photometric stereo is a technique for estimating surface normals in order to calculate a 3D topography of that surface. The technique was originally introduced by Woodham in 1980. [1] The surface normals are calculated by observing an object from different illumination directions. With each direction, the object casts different shadows on the surface and a camera acquires images for each illumination (Figure 1).

Using shape from shading, the surface curvature is estimated, and the height map of the object can be calculated. The result is a real 3D topography of the measured object surface (Figure 2).

Image acquisition of different illuminations to calculate surface topography

Figure 1: Image acquisition of different lluminations to calculate surface topography [2]

Height map of a powder coated surface

Figure 2: Height map of a powder coated surface measured with the spectro2profiler instrument. The unit P-µm is perceived height.

Watershed analysis to define structure cell sizes

Topographies such as leather grains or coarse powder coated structures can be characterized by their structure cells. To divide the topography into cells, the watershed algorithm is used, a region-based segmentation approach. One can imagine that the algorithm gradually floods the valleys of the topography, building rivers until hill areas are surrounded. [3] These areas will be defined as cells, marked as green lines in Figure 3.

Raw data and segmented topography data of a leather grain on a plastic substrate

Figure 3: Raw data and segmented topography data of a leather grain on a plastic substrate

Characteristic features of the surface can be calculated based on the watershed segmentation results to compare different structures or grains. Spatial length scales result from camera calibration and are traceable to SI-units. The calculated average cell size correlates to our visual impression of coarseness. The distribution of individual cell sizes is an indication for the uniformity of the surface structure. For example, a natural leather structure varies in uniformity depending on the part of the cow skin. A textured paint can form agglomerations during the wet paint application, if the application parameters vary resulting in an inhomogeneous appearance. The normalized cell size deviation is calculated by dividing the cell size distribution with the mean cell size. It is an objective measure to compare the uniformity of different structures independent of its absolute cell size.

Conventional measurement of reflectivity and gloss

Reflectivity and gloss are based on the interaction of light with the physical properties of the sample surface. The intensity is dependent on the material and the angle of illumination. The measurement results of a conventional glossmeter are related to the amount of reflected light from a black glass standard with a defined refractive index. Today's measuring instruments are very precise and widely used in industry, but they hold some weak points in the measurement of structured surfaces. Cast shadows and areas that are invisible to the measurement detector can falsify the measurement result. Moreover, the perception of gloss does not only depend on specular gloss but also on the observed contrast between specular highlights and diffusely reflecting surface areas. [4] A conventional gloss meter is not capable to capture more complex reflective behaviour such as spatially distributed reflections e.g. high reflecting hills next to low reflecting valleys which occur in leather-like structures.

Spatially resolved 2D reflectivity measurement

The portable instrument spectro2profiler from BYK-Gardner (Figure 4) offers a new camera-based technology to capture the spatial distribution of reflectivity.

An in-line illumination setup eliminates cast shadows, invisible areas and perspective distortions so that the measurement is independent of orientation (Figure 5).

Color, gloss, 3D topography and 2D reflectivity of structured surfaces

Figure 4: The measuring device can be used to determine the color, gloss, 3D topography and 2D reflectivity of structured surfaces.

Setup of spatial resolved reflectivity measurement

Figure 5: Setup of spatial resolved reflectivity measurement.

Reflectivity map of a powder coated surface acquired with the spectro2profiler

Figure 6: Reflectivity map of a powder coated surface acquired with the spectro2profiler

The camera acquires 2D reflectivity images. Figure 6 shows a grey scaled reflectivity map in which every pixel represents a reflectivity value allowing more detailed analysis of reflectivity distributions of a surface.

Combination of 3D topography data with 2D reflectivity data

In order to assess the overall appearance of an object, it is necessary to measure surface structure and reflectivity in parallel, as they are mutually interdependent, but are combined for an overall visual assessment. [5] Because our eyes are only capable to acquire 2D information, the human visual system reconstructs 3D information of objects in our brain using shading and reflections. [6] That means, the perceived depth of a structure is dependent on the reflection behaviour on the hills and valleys.

Since the spectro2profiler uses the same camera and lens system for the acquisition of 3D topography and 2D reflectivity data, it is possible to combine the data of both measurement principles. Thus, the reflection of hills and valleys can be separated. The difference between reflection of hills and valleys, describes the contrast and perceived depth of a structured surface.

A practical example as found in the automotive industry

Many automotive interior components have a leather-like look and are manufactured by different suppliers with different processes and made of various materials. The appearance of the products surface is analyzed in the different development phases, e.g. at the very beginning by the design department in the grain development to approve suppliers and at the very end by quality control in production.Leather grain structures can appear different in contrast although color and 60° gloss are the same (Figure 7).

Four dashboard slush skins of same material with different levels of contrast

Figure 7: Four dashboard slush skins of same material with different levels of contrast

This can be caused due to different reflectivity levels of the surface on hills and valleys. Up till now this had to be evaluated visually which is subjective and non-repeatable. The results in Table 1 show how the reflectivity contrast Rc distinguished the samples despite having the same color and 60° Gloss. Moreover, the results of the reflectivity for hills and valleys provide details about what causes the different reflectivity contrasts.

Checkzone Sample 1 Sample 2 Sample 3 Sample 4
Mean Reflectivity R (a.u.) 162 156 156 155
Reflectivity Hills Rh (a.u.) 209 188 195 190
Reflectivity Valleys Rv (a.u.) 115 122 115 117
Reflectivity Contrast Rc 0.29 0.21 0.26 0.24
Gloss 60° (GU) 1.3 1.3 1.2 1.3
Table 1: Reflectivity and gloss results of four leather grains of same grain type


New spectro2profiler is a game changer and marks a turning point in the analysis of structured surfaces. The combination of color, gloss, 3D topography and 2D reflectivity in one easy to use instrument is a milestone in the objective measurement control of textured surfaces. At this moment, the spectro2profiler incorporates three algorithms for surface structure analysis: Leather-like structures, coarse paint textures and fine paint or plastic textures. Due to its excellent technical performance in regards to repeatability and inter-instrument agreement, digital standards can be used as a reference, allowing a flawless communication within a global supply chain.

From now on, our visual perception of colour, gloss and structure can be evaluated in a holistic and objective approach, color and appearance harmony when combining different components can be optimized and all this is possible in the laboratory as well as on the production line with the portable spectro2profiler.


  • [1] Woodham, R.J. 1980. Photometric method for determining surface orientation from multiple images. Optical Engineerings 19, I, 139-144

  • [2] Serge Beucher and Christian Lantuéj workshop on image processing, real-time edge and motion detection (1979).

  • [3] Hunter, R. S. (1937). Methods of determining gloss. Journal of Research of the National Bureau of Standards, 18(1), 19–41

  • [4] Qi, L., Chantler, M. J., Siebert, J. P., & Dong, J. (2012). How mesoscale and microscale roughness affect perceived gloss. Edinburgh, Scotland: Lulu Press, Inc.

  • [5] A. Nischwitz et al., Computergrafik und Bildverarbeitung, Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH 2011


  • Dr. Christopher Groh

  • Jonas Harmeling

  • Gabriele Kigle-Böckler

  • BYK-Gardner GmbH, Geretsried / Germany

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