On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multichannel Approach to Fingerprint Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Classification by Directional Image Partitioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
A Structural Approach to Fingerprint Classification
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
FVC2002: Second Fingerprint Verification Competition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Fingerprint classification based on decision tree from singular points and orientation field
Expert Systems with Applications: An International Journal
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Large scale, automatic fingerprint identification systems (AFISs) perform fingerprint classification to improve matching accuracy and reduce the matching time before fingerprint matching. Fingerprints are classified into several classes such as arch (A), whorl (W), left loop (L) and right loop (L). The existing systems generally classify fingerprints based on the information of singular points. This approach is well suited for fingerprints acquired using paper and ink. However, it is not as efficient with recent automatic fingerprint systems because it cannot guarantee that singular points are well extracted since the recent systems have various sized sensors and use multifarious fingerprint acquisition methods. In this paper, a novel approach is proposed to use the fingerprint ridge direction, which is one of the global features. It is a probabilistic approach based on the fingerprint ridge characteristics of each class. FVC2000 DB1 and FVC2002 DB1 databases were used to evaluate the performance of our classification. Furthermore, the effectiveness of applying the probabilistic model to the classification of various exceptional fingerprint patterns was verified.