Biometric Identification through Hand Geometry Measurements
IEEE Transactions on Pattern Analysis and Machine Intelligence
Peg-Free Hand Shape Verification Using High Order Zernike Moments
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach
Neural Processing Letters
Model-guided deformable hand shape recognition without positioning aids
Pattern Recognition
Personal verification using palmprint and hand geometry biometric
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
| Hi-index | 0.00 |
While locating the points used for obtaining the hand-shape features with high class separability, the stability of the point positions is easily influenced by the hand positions and the wearing decorations. This paper improves the linear fitting accurate location method through removing the interference of parts of the experience values. It can reduce the impact of fingers flexibility and improve the accuracy of the finger-tip and finger-root points. In addition, the paper proposes a revised method to locate the wrist point. And the palm length can be used for automatic identification as one of the features in the vector. The experiments can verify the stability of the method through the standard deviation mean. Through the contrast of the matching results between the automatic and artificial measurement, the D-value is 0.7% of the 3-feature vector and 0.4% of 6-feature vector. It can prove the feasibility of the location method used the peg-free images.