Automated human age estimation at death via bone microstructures

This paper present a proposed method for automatic human age at death estimation using image processing and pattern recognition techniques. The bone samples are taken from ulna, radius, humerus, femur, tibia and fibula of Malaysian population. Ten different bone microstructures are selected for analysis in order to create regression equation for age estimation. Selected microstructure can be extracted using image preprocessing and texture extraction algorithms. Different classification methods are proposed for automatic human age estimation in Malaysian population. This paper provide significant implications in the computation of fragmentary skeletal remains and forensic population samples for age estimation purpose.