Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
A direct method for stereo correspondence based on singular value decomposition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Online Palmprint Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fisherpalms based palmprint recognition
Pattern Recognition Letters
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Palmprint Authentication (International Series on Biometrics)
Palmprint Authentication (International Series on Biometrics)
Palmprint identification using feature-level fusion
Pattern Recognition
Palmprint verification based on robust line orientation code
Pattern Recognition
Local invariant feature detectors: a survey
Foundations and Trends® in Computer Graphics and Vision
A survey of palmprint recognition
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Palmprint verification using binary orientation co-occurrence vector
Pattern Recognition Letters
Multifeature-Based High-Resolution Palmprint Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel sparse representation based classification
Neurocomputing
Analysis of performance of palmprint matching with enforced sparsity
Digital Signal Processing
Palmprint based recognition system using phase-difference information
Future Generation Computer Systems
Robust and Efficient Ridge-Based Palmprint Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.00 |
In this paper, a new palmprint matching system based on the extraction of feature points is suggested. Using a scale-space representation, the points in question are corners formed by the intersection of creases and lines. Unlike minutiae, such points can still be extracted even on low resolution palmprints. Matching is carried out using an SVD factorisation of a proximity matrix and takes account of the coordinates of the detected points and their local texture. Our experiments have yielded some very good results evidenced by an EER of 0.10%.