LSP based comparison of 3D ear models

Ear biometric authentication is considered to be an important aspect of human identification and is, among other techniques, used in victim identification for practical reasons. State-of-the-art techniques transform 2D ear photos to 3D ear models to adequately cope with geometrical and photometric normalisation issues. From each 3D ear model a feature list is extracted and used in the comparison process. In this paper we study how automated comparison of 3D ear models can be improved by soft computing techniques. More specifically we investigate and illustrate how multiple-criteria decision support techniques, which are based on fuzzy set theory, can be used for fine-tuning the ear comparison process. Point-to-point matching schemes are enriched with Logic Scoring of Preference (LSP) multiple-criteria decision support facilities. In this way valuable knowledge of forensic experts on ear identification aspects can be incorporated in the comparison process. The benefits and added value of the approach are discussed and demonstrated by an illustrative example.