Conference paper
Quality Estimation for Vascular Pattern Recognition
The quality of captured samples is a critical aspect in biometric systems. In this paper we present a quality estimation algorithm for vascular images, which uses global and local features based on a Grey Level Co-Occurrence Matrix (GLCM) and optionally available metadata. An evaluation of the algorithm using different processing methods and vein sample databases shows convincing results: disregarding low estimated quality sample images helps to increase the performance.
Moreover, metadata gives accurate indications on sample quality. The algorithm works on low level raw images, it is fast and therefore qualified to be used in feedback mode during enrolment or verification operation.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2011 |
| Pages: | 1-6 |
| Proceedings: | International Conference on Hand-Based Biometrics |
| ISBN: | 1457704897 , 1457704900 , 1457704919 , 9781457704895 , 9781457704901 and 9781457704918 |
| Types: | Conference paper |
| DOI: | 10.1109/ICHB.2011.6094332 |
Algorithm design and analysis Correlation Databases Estimation GLCM Iris recognition Quality assessment Veins biometric systems feature extraction global features grey level cooccurrence matrix image quality local features matrix algebra meta data metadata quality estimation algorithm vascular images vascular pattern recognition vein recognition vein sample databases visual databases
