Evidence-Based Complementary and Alternative Medicine

Evidence-Based Complementary and Alternative Medicine / 2009 / Article

Original Article | Open Access

Volume 6 |Article ID 319742 | https://doi.org/10.1093/ecam/nep065

Imhoi Koo, Jong Yeol Kim, Myoung Geun Kim, Keun Ho Kim, "Feature Selection from a Facial Image for Distinction of Sasang Constitution", Evidence-Based Complementary and Alternative Medicine, vol. 6, Article ID 319742, 7 pages, 2009. https://doi.org/10.1093/ecam/nep065

Feature Selection from a Facial Image for Distinction of Sasang Constitution

Received16 Mar 2009
Accepted21 May 2009


Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

Copyright © 2009 Imhoi Koo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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