Reconstructing Orientation Field From Fingerprint Minutiae to Improve Minutiae-Matching Accuracy 吳思穎

Introduction Tradition : store the minutiae template in the database. -> include two step : 1. minutiae extraction 2. minutiae matching This paper : reconstructing fingerprint’s orientation field from minutiae and further utilizing it in the matching stage to enhance the system’s performance. fusing the results of orientation field matching with conventional minutiae-based matching.

Fig. 1. Flowchart of the proposed algorithm.

Section II : the algorithm of reconstructing orientation field Section III : the algorithm of fingerprint recognition by minutiae and orientation field. Section IV : experimental results Section V : conclusion and discussion

The algorithm of reconstructing orientation field Interpolation Reconstruction Using an Orientation Model

Interpolation Triangulation Use Delaunay triangulation

Interpolation Producing “virtual” minutiae using interpolation (1) (2)

Interpolation Producing “virtual” minutiae using interpolation (3) (4)

Reconstruction Using an Orientation Model Polynomial model Reconstruction the orientation field using polynomial model

Fig. 5. Results of the proposed algorithm: (a) virtual minutiae by interpolation (the bigger red minutiae are “real,, while the smaller purple ones are “virtual,); (b) the reconstructed orientation field.

Fig. 6. Comparison result I: (a ） minutiae image with a wrong direction (marked with ellipse ） ; (b ） the corresponding poor result by interpolation (marked with ellipse ) ; (c ） the corresponding good result by the proposed IM method.

Fig. 7. Comparison result II: (a ） minutiae image with a sparse region (marked with ellipse ） ; (b ） the corresponding poor result by model-based algorithm (marked with ellipse ） ; (c ） the corresponding good result by the proposed IM method.

The algorithm of fingerprint recognition by minutiae and orientation field.

experimental results conclusion and discussion