Geometrical local image descriptors for palmprint recognition

Bilal Attallah (1, 2) , Youssef Chahir (1) , Amina Serir (2)

1 Equipe Image - Laboratoire GREYC - UMR6072
2 USTHB - Université des Sciences et de la Technologie Houari Boumediene = University of Sciences and Technology Houari Boumediene [Alger]

A new palmprint recognition system is presented here. The method of extracting and evaluating textural feature vectors from palmprint images is tested on the PolyU database. Furthermore, this method is compared against other approaches described in the literature that are founded on binary pattern descriptors combined with spiral-feature extraction. This novel system of palm-print recognition was evaluated for its collision test performance, precision, recall , F-score and accuracy. The results indicate the method is sound and comparable to others already in use.

Mots clés: fusion; Biometrics; Palm print recognition; Texture features; BSIF; Spiral features

Domaines: Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]

Bilal Attallah, Youssef Chahir, Amina Serir. Geometrical local image descriptors for palmprint recognition. International Conference on Image and Signal Processing 2018 (ICISP 2018), Jul 2018, Cherbourg, France. pp.419-426, ⟨10.1007/978-3-319-94211-7_45⟩. ⟨hal-01790993⟩