Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification

By N. Miura, Akio Nagasaka, T. Miyatake. Machine Vision and Applications, 2004

653 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/370ff1f9bbce86e404e37da774bf51a05af423a7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yingbo Zhou
2. Ajay Kumar
3. Frauke Günther

In Signal Processing

1. Yingbo Zhou
2. Ajay Kumar
3. Frauke Günther

Citations in the corpus

• Human Identification Using Finger Images (2012, methodology): “The poor performance (table 2 and figure 15) of line tracking and maximum curvature in the vein database [26] can also be attributed to the fact that the ambiguous regions [5] contributed large areas in the extracted vein feature representations.”