Ningfang Liao

Investigation of Chinese skin colour and appearance for skin colour reproduction

A Chinese skin colour database is established based on measurements taken from nine bodies areas of 202 Chinese individuals to move towards accurate skin colour reproduction. The colour appearance of each skin point is predicted, and a comprehensive colour gamut for Chinese skin is determined. A consistent colour shift between facial and arm colours is identified, in which facial colour tends to be more reddish, more colourful, and darker than arm colour. Moreover, Chinese females are found to have lighter, paler, and more yellowish skin than Chinese males. Variations in Chinese skin colour are quantified, and body area differences and gender differences are shown to have significant effects on Chinese skin colour.

Characterising the variations in ethnic skin colours: a new calibrated data base for human skin

Accurate skin colour measurements are important for numerous medical applications including the diagnosis and treatment of cutaneous disorders and the provision of maxillofacial soft tissue prostheses.

A CRT monitor ICC profile based on matrix-look-up-table model

The goal of ICC (International color consortium) color management system (CMS) is to reproduce color fidelity regardless of the hardware or platform used to capture, view or print them. The accuracy of profiles decides the precision of color conversion; therefore, creating device profiles accurately is very essential for color management. In this paper, according to the ICC standard format, we used Matrix-LUT (look up table) model, which can increase the color conversion precision to create monitor profile. In laboratory environment, we used X-Rite DPT92 to calibrate the monitor, and then we made about 1000 color patches and measured the RGB and the corresponding XYZ of each patch. We adopted linear interpolation method to establish the LUT between RGB and XYZ. The experimental results are good, and then we finished the monitor profile by the ICC format, realized CRT monitor color management.

Implementing color transformation across media based on color appearance model by neural networks

Interest in color appearance models (CAM) has been greatly stimulated recently by the need in handling digital images. This article demonstrates that a multi-layers feed-forward artificial neural network with the error back-propagation algorithm was used to approximate color appearance model CIECAM02 with different white points and different media. For the prediction of the forward and inverse model respectively, in order to realize accurate mapping, especially to the inverse model, color spaces conversion between input color space and output color space (that is cylindrical coordinates and rectangular coordinates) was implemented before training the neural networks. Meanwhile we approximated the combination of the forward and inverse CIECAM02 models employing a neural network for different conditions including whites (D65 or D50) and media (booth and CRT) in order to realize the color transformation from one medium to another conveniently. The experimental results indicated that the prediction could satisfy the accuracy requirement. So in practice we can choose these two kinds of different prediction ways to meet our need according to different situations.

Study on Acceptable Color Difference Using Printed Samples

The psychophysical method of constant stimuli and the gray scale were made to study the acceptable color difference of the printed samples, which were arounded the 17 color centers with the same lightness CIE proposed. The experimental results showed that the CIE1976 a-bplane is visually non-uniform, and there is no obvious discrepancy between the perceptible and acceptable color difference threshold. In terms of the linear correlation coefficient r, the CIEDE2000 color difference formula outperformed CIELAB, CMC, CIE94 with the best matching with visual evaluations greatly. Keywordsvision and color; acceptable color difference; chromaticity ellipses; color-difference formulae

Visual modeling of cathode ray tube displays for finding cross-media corresponding colors based on the natural color system color atlas and neural networks

A visual method for characterizing cathode ray tube (CRT) displays and finding corresponding colors is presented. The method is motivated by the considerable expense of measuring instruments and the consideration of color appearance factors. In the experiment, a set of color chips in the natural color system (NCS) color atlas, an illuminant, and a CRT are used. 487 sample pairs of RGB (CRT) and HVC, which are the attributes of NCS color chips, are obtained by experimentally comparing softcopies and hardcopies in the office environment in the sense of best color matching to nine observers. Both the spectral data of the color chips and the colorimetric values of the CRT samples are measured. In addition, 12 error back-propagation (BP) neural networks are trained to help the realization of the transformation from HVC to RGB for data generalization. The current results show that the displays on the CRT can match the chips in color perception well.