Modelling texture appearance of gonioapparent objects (2008)

Quantifying the appearance of coating products is essential in the automobile and&#13;\nautomobile finishing industries for efficient product development and product/quality&#13;\ncontrol. There is a specific need to develop techniques to measure the total appearance&#13;\nof metallic coatings. The present study focuses on two key attributes of visual texture:&#13;\ncoarseness and glint. In order to develop models to capable of measuring these&#13;\nattributes, it was first necessary to design psychophysical experiments for assessing&#13;\ncoarseness and glint as perceived on metallic-coating panels. The change in the&#13;\nappearance of the metallic coatings is known as a gonioapparent effect, and is greatly&#13;\ndependant on the illumination and viewing conditions. Therefore, appropriate&#13;\nconditions were carefully examined for the independent observation of coarseness and&#13;\nglint in order to discern those attributes. It was found that diffuse illumination was&#13;\nappropriate for viewing coarseness and directional illumination was appropriate for&#13;\nobserving glint. Under these appropriately-controlled conditions, the perceptual&#13;\ncoarseness and glint of sets of metallic-coating panels were assessed by human&#13;\nobservers.&#13;\nA digital camera was used to capture information on the spatial detail of the&#13;\nmetallic-coating panels. An image of each panel was captured under the same viewing&#13;\nconditions as used for the visual assessments. The information in a single image was&#13;\nsufficient to represent a metallic-coating panel under identical diffuse illumination&#13;\nconditions for which observers assessed coarseness. For capturing information on glint,&#13;\nhowever, a high dynamic-range (HDR) image was necessary because the dynamic range&#13;\nof the scene in which the glint was observed exceeded that of the camera used in this&#13;\nstudy. Two computational models were developed to predict perceptual coarseness and&#13;\nperceptual glint by extracting associated features from the captured images. The&#13;\nperformance of these models was verified by comparing predictions made using them&#13;\nwith the perceptual coarseness and glint scaled by observers.&#13;\nFor industrial use, the visualisation of products on computer displays would give&#13;\nvarious opportunities, for example, to develop and design products or coatings and also&#13;\nto communicate appearance information. A digital camera and a suitable display would&#13;\nenable this to be achieved, but the ability to reproduce the appearance of metallic-coating&#13;\nproducts on displays in a satisfactory manner was found to have significant&#13;\n~&#13;\nchallenges. The coarseness model developed in the present study was able to represent&#13;\nperceptual coarseness based on the images captured by the digital camera. However,&#13;\nthe resolution of the images was not high enough to resolve the individual aluminium&#13;\nflakes contained in the coatings, which contribute to the visual texture. Therefore,&#13;\nverification of the images was carried out for the coarseness attribute by comparing the&#13;\ncoarseness perceived in the images displayed on a liquid-crystal display (LCD) with the&#13;\nmetallic-coating panels themselves. In addition to camera limitations, LCD resolution&#13;\nalso prevented the same conditions used for physical panel assessment from being&#13;\nreplicated. Therefore, two optimal conditions were selected and perceptual coarseness&#13;\nwas scaled using images. Besides the difference in experimental conditions, there was&#13;\nalso a difference in the "absolute" texture appearance between the two media because of&#13;\nerrors in image reproduction of the images. In spite of this, the relatively-scaled&#13;\nperceptual coarseness for the image samples agreed well with that for the original&#13;\nphysical samples. This implies that it is practicable to assess perceptual coarseness&#13;\nfrom an image on a display that simulates a metallic-coating panel&#13;\n