Fingerprint identification using graph matching
Pattern Recognition
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fingerprint Matching Using an Orientation-Based Minutia Descriptor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Feature Extraction Method for Palmprint Considering Elimination of Creases
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
A SIFT Descriptor with Global Context
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Fingerprint minutiae matching using the adjacent feature vector
Pattern Recognition Letters
Minutiae-based partial fingerprint recognition
Minutiae-based partial fingerprint recognition
On the Use of SIFT Features for Face Authentication
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
IIH-MSP '08 Proceedings of the 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing
A robust method for partial deformed fingerprints verification using genetic algorithm
Expert Systems with Applications: An International Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment andminutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposedwhere the partial palmprint's minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to eachminutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained showthat the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.