Continuous fingerprints classification by symmetrical filters

ABSTRACT

In a large number of fingerprint database, the naïve way to identify a person is to match the query image with all entries of the database. To speed up this processing, exclusive classification assigns each fingerprint into one of several subgroups. Thus the query image only needs to compare with the images in one subgroup. While exclusive classification is hard because of small inter-class variability and the large intra-class variability. And it is not so efficient as well due to the small number of classes and non-uniform distribution.

REFERENCES

• 1: Raffaele Cappelli , Alessandra Lumini , Dario Maio , Davide Maltoni, Fingerprint Classification by Directional Image Partitioning, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.21 n.5, p.402-421, May 1999 [doi>10.1109/34.765653 ]
• 2: Bir Bhanu , Xuejun Tan, Fingerprint Indexing Based on Novel Features of Minutiae Triplets, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.25 n.5, p.616-622, May 2003 [doi>10.1109/TPAMI.2003.1195995]
• 3: J. d. Boer, A. Bazen, and S. Gerez, Indexing fingerprint databases based on multiple features, in Workshop on Circuits, Systems and Signal Processing, 2001.
• 4: Kenneth Nilsson , Josef Bigun, Localization of corresponding points in fingerprints by complex filtering, Pattern Recognition Letters, v.24 n.13, p.2135-2144, September 2003 [doi>10.1016/S0167-8655(03)00083-7]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.7 Feature Measurement
      I.4.9 Applications

General Terms:
Algorithms, Security

Keywords:
continuous fingerprints classification