Abstract An automated Chinese female facial beauty classification approach is presented through the application of machine learning algorithm of C4.5. Seventeen geometric features are designed to abstractly represent each facial image. With large set of 510 Chinese female facial images, high average accuracy of 94.1% is obtained for two-level classification－beautiful or not, and the average accuracy of 4-level classification is 71.6%. The results show that the notion of beauty perceived by human can also be learned by machine through using machine learning techniques.
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2010, Vol. 23 
