Minutia Confidence Index: a new framework to qualify minutia usefulness

Lobna Makni (1) , Christophe Charrier (2)

1 UNICAEN - Université de Caen Normandie
2 Equipe SAFE - Laboratoire GREYC - UMR6072

Due to the advantages in privacy and efficiency requirements, minutiae template based matching is the dominant technique among the authentication approaches of fingerprint image and its performance fully relies on the quality of the input fingerprint image. In this case, it is reasonable to consider qualifying fingerprint with fingerprint minutiae template information extracted from fingerprint image, particularly when using for embedded applications due the limited memory. In fact, the speed of fingerprint recognition increases with the decrease of the size of database. For these reasons, a new confidence measure called Minutia Confidence Index (MiCI) for each minutia of the template is proposed. This index predicts the importance and the usefulness of each minutia with respect to the others in the template. It takes into account only minutiae template information (i.e., x and y coordinates, the type and the orientation). MiCI score is a value between 0 and 1, where highest values are for the mostly relevant minutiae in the template whereas lowest values are for less important ones. This measure has been applied in the template reduction use case on Fingerprint Verification Competition (FVC) and SFINGE0 databases and demonstrated its capability to reach high performance.

Domaines: Cryptographie et sécurité [cs.CR]; Traitement des images [eess.IV]; Traitement du signal et de l'image [eess.SP]

Lobna Makni, Christophe Charrier. Minutia Confidence Index: a new framework to qualify minutia usefulness. International Conference Cyberworlds 2020, Sep 2020, Caen, France. ⟨hal-02928589⟩