Age estimation based on local radon features of facial images

Abstract

This paper proposes a new age estimation method relying on regional Radon features of facial images and regression. Radon transform converts a pixel represented image an equivalent, lower dimensional and more geometrically informative Radon pixel image and it brings a large advantage achieving global geometric affine invariance. Proposed method consists of four modules: preprocessing, feature extraction with Radon transform, dimensionality reduction with PCA and age estimation with multiple linear regression. We conduct our experiments on FG-NET, MORPH and FERET databases and the results have shown that proposed method has better results than many conventional methods on all databases. © 2013 Springer-Verlag London.