Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles

By N. Miura, Akio Nagasaka, T. Miyatake. IAPR International Workshop on Machine Vision Applications, 2007

681 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/85c3f43392598a2029ceda1bb2b5ea1d5236555f

How researchers see this paper

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

In Artificial Intelligence

1. John K. Tsotsos
2. Ajay Kumar
3. Alexander Andreopoulos
4. Yingbo Zhou

In Computer Vision and Pattern Recognition

1. John K. Tsotsos
2. Yingbo Zhou
3. Alexander Andreopoulos
4. Ajay Kumar
5. Junwei Han
6. Dacheng Tao
7. Gong Cheng
8. Graham W. Taylor

In Radiology, Nuclear Medicine and Imaging

1. John K. Tsotsos
2. Alexander Andreopoulos

Citations in the corpus

• Human Identification Using Finger Images (2012, background): “The robustness in the extraction of finger-vein patterns can be significantly improved with the use of local maximum curvature across the vein images and is detailed in [6] with promising results.”
• 50 Years of object recognition: Directions forward (2013, background): “Biometric vision-based systems for fingerprint recognition [17], iris pattern recognition [18], as well as finger-vein and palm-vein patterns [19, 20] have also gained acceptance by the law enforcement community and are widely used.”