Fingerprint pattern classification
Pattern Recognition
A Real-Time Matching System for Large Fingerprint Databases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Joint Induction of Shape Features and Tree Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Continuous versus exclusive classification for fingerprint retrieval
Pattern Recognition Letters
An Off-Line Cursive Handwriting Recognition System
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
Fingerprint Preselection Using Eigenfeatures
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern 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
Initialization of hidden Markov models for unconstrained on-line handwriting recognition
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06
Fingerprint Indexing Based on Novel Features of Minutiae Triplets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A two-stage fingerprint classification system
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Classifier geometrical characteristic comparison and its application in classifier selection
Pattern Recognition Letters
Efficient fingerprint search based on database clustering
Pattern Recognition
From Template to Image: Reconstructing Fingerprints from Minutiae Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
The VLDB Journal — The International Journal on Very Large Data Bases
Calligraphic Interfaces: Classifier combination for sketch-based 3D part retrieval
Computers and Graphics
Level 2 features and wavelet analysis based hybrid fingerprint matcher
COMPUTE '08 Proceedings of the 1st Bangalore Annual Compute Conference
Enhanced SEA algorithm and fingerprint classification
International Journal of Computer Applications in Technology
Gabor Filter-Based Fingerprint Anti-spoofing
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Ridgelet-based fake fingerprint detection
Neurocomputing
Fingerprint classification based on Adaboost learning from singularity features
Pattern Recognition
Dynamically subsumed-OVA SVMs for fingerprint classification
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Learning features for fingerprint classification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A probability-based unified 3d shape search
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
Effective fingerprint classification by localized models of support vector machines
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A near-linear time algorithm for binarization of fingerprint images using distance transform
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Environmentally realistic fingerprint-image generation with evolutionary filter-bank optimization
Expert Systems with Applications: An International Journal
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Fingerprint classifier using embedded hidden markov models
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
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Fingerprint classification is an important indexing method for any large scale fingerprint recognition system or database as a method for reducing the number of fingerprints that need to be searched when looking for a matching print. Fingerprints are generally classified into broad categories based on global characteristics. This paper describes novel methods of classification using hidden Markov models (HMMs) and decision trees to recognize the ridge structure of the print, without needing to detect singular points. The methods are compared and combined with a standard fingerprint classification algorithm and results for the combination are presented using a standard database of fingerprint images. The paper also describes a method for achieving any level of accuracy required of the system by sacrificing the efficiency of the classifier. The accuracy of the combination classifier is shown to be higher than that of two state-of-the-art systems tested under the same conditions.