1 March 2005 Determination of optimal view angles for quantitative facial image analysis
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J. of Biomedical Optics, 10(2), 024002 (2005). doi:10.1117/1.1895987
Abstract
In quantitative evaluation of facial skin chromophore content using color imaging, several factors such as view angle and facial curvature affect the accuracy of measured values. To determine the influence of view angle and facial curvature on the accuracy of quantitative image analysis, we acquire cross-polarized diffuse reflectance color images of a white-patched mannequin head model and human subjects while varying the angular position of the head with respect to the image acquisition system. With the mannequin head model, the coefficient of variance (CV) is determined to specify an optimal view angle resulting in a relatively uniform light distribution on the region of interest (ROI). Our results indicate that view angle and facial curvature influence the accuracy of the recorded color information and quantitative image analysis. Moreover, there exists an optimal view angle that minimizes the artifacts in color determination resulting from facial curvature. In a specific ROI, the CV is less in smaller regions than in larger regions, and in relatively flat regions. In clinical application, our results suggest that view angle affects the quantitative assessment of port wine stain (PWS) skin erythema, emphasizing the importance of using the optimal view angle to minimize artifacts caused by nonuniform light distribution on the ROI. From these results, we propose that optimal view angles can be identified using the mannequin head model to image specific regions of interest on the face of human subjects.
Byungjo Jung, Bernard Choi, Yongjin Shin, Anthony Joseph Durkin, John Stuart Nelson, "Determination of optimal view angles for quantitative facial image analysis," Journal of Biomedical Optics 10(2), 024002 (1 March 2005). http://dx.doi.org/10.1117/1.1895987
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KEYWORDS
Skin

Head

Diffuse reflectance spectroscopy

Human subjects

Image analysis

Imaging systems

RGB color model

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