Automated facial metrology is the science of objective and automatic measurement of the human face. There are many reasons for measuring the human face. Psychologists are interested in determining how humans perceive beauty, and how this is related to facial symmetry [158]. Biologists are interested in the relationship between symmetry and biological fitness [124]. Anthropologists, surgeons, forensic experts, and security professionals can also benefit from automated facial metrology [32, 101, 114]. This thesis investigates the concept of automated facial metrology, presenting original techniques for segmenting 3D range and colour images of the human head, measuring the bilateral symmetry of n-dimensional point data (with particular emphasis on measuring the human head), and extracting the 2D profile of the face from 3D data representing the head. Two facial profile analysis techniques are also presented that are incremental improvements over existing techniques. Extensive literature reviews of skin colour modelling, symmetry detection, symmetry measurement, and facial profile analysis are also included in this thesis. It was discovered during this research that bilateral symmetry detection using principal axes is not appropriate for detecting the mid-line of the human face. An original mid-line detection technique that does not use symmetry, and is superior to the symmetry-based technique, was developed as a direct result of this discovery. There is disagreement among researchers about the effect of ethnicity on skin colour. Some researchers claim that people from different ethnic groups have the same skin chromaticity (hue, saturation) [87, 129, 206], while other researchers claim that different ethnic groups have different skin colours [208, 209]. It is shown in this thesis that people from apparently different ethnic groups can have skin chromaticity that is within the same Gaussian distribution. The chromaticity-based skin colour model used in this thesis has been chosen from the many models previously used by other researchers, and its applicability to skin colour modelling has been justified. It is proven in this thesis that the Mahalanobis distance to the skin colour distribution is Gaussian in both the chromatic and normalised rg colour spaces. Most facial profile analysis techniques use either tangency or curvature to locate anthropometric features along the profile. Techniques based on both approaches have been implemented and compared. Neither approach is clearly superior to the other, but the results indicate that a hybrid technique, combining both approaches, could provide significant improvements. The areas of research most relevant to facial metrology are reviewed in this thesis and original contributions are made to the body of knowledge in each area. The techniques, results, literature reviews, and suggestions presented in this thesis provide a solid foundation for further research and hopefully bring the goal of automated facial metrology a little closer to being achieved.