Name
Title | ||
|---|---|---|
A First Step to Accelerating Fingerprint Matching Based on Deformable Minutiae Clustering. |
Abstract | ||
|---|---|---|
Fingerprint recognition is one of the most used biometric methods for authentication. The identification of a query fingerprint requires matching its minutiae against every minutiae of all the fingerprints of the database. The state-of-the-art matching algorithms are costly, from a computational point of view, and inefficient on large datasets. In this work, we include faster methods to accelerating DMC ( the most accurate fingerprint matching algorithm based only on minutiae). In particular, we translate into C++ the functions of the algorithm which represent the most costly tasks of the code; we create a library with the new code and we link the library to the original C# code using a CLR Class Library project by means of a C++/CLI Wrapper. Our solution re-implements critical functions, e.g., the bit population count including a fast C++ PopCount library and the use of the squared Euclidean distance for calculating the minutiae neighborhood. The experimental results show a significant reduction of the execution time in the optimized functions of the matching algorithm. Finally, a novel approach to improve the matching algorithm, considering cache memory blocking and parallel data processing, is presented as future work. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00374-6_34 | ADVANCES IN ARTIFICIAL INTELLIGENCE, CAEPIA 2018 |
Keywords | DocType | Volume |
Fingerprint recognition,Cache optimization,Language interoperability | Conference | 11160 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andres Jesus Sanchez | 1 | 0 | 0.34 |
| Luis Felipe Romero | 2 | 10 | 1.33 |
| Siham Tabik | 3 | 167 | 18.92 |
| Miguel Angel Medina-pérez | 4 | 85 | 10.93 |
| Francisco Herrera | 5 | 27391 | 1168.49 |