Abstract
The evaluation and measurement of human body dimensions are achieved by physical anthropometry. The main goal of this research is to optimization of facial feature point by establishing a mathematical relationship among facial features and used optimize feature points for age classification. According to this proposes method, sixteen Euclidean distances are calculated from the eighteen selected facial feature points vertically as well as horizontally. The distances between the specified features points increase with respect the age progression of a human from his or her childhood but the ratio of the distances does not change ( =1.618). Feature distances are used for classification of age using Support Vector Machine (SVM) - Sequential Minimal Optimization (SMO) algorithm and shown around 96% accuracy.
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