Classification of Age from Facial Features of Humans

This writing presents a new way for classification of human age based on k-NN classifier. The hypothesis has been implemented to distribute input images into one of four age groups i. e kid, young, adult and senior adult. For implementation, first primitive features of face supported on craniofacial development is found. For subordinate features skin texture and wrinkle analysis is found. Images from FGNET database are used to differentiate babies from other groups based on geometrical ratios. The other three groups are classified by LBP for skin texture and Gabor for wrinkles analysis. Finally, age group are categorized by using k-NN classifier.