Title :
Multi-angle sclera recognition system
Author :
Zhou, Zhi ; Du, Eliza Yingzi ; Thomas, N. Luke ; Delp, Edward J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Indiana Univ., Indianapolis, IN, USA
Abstract :
Sclera patterns can be used for human classification and identification; however image quality can significantly affect the recognition accuracy. In this paper, we studied and analyzed four multi-angle sclera recognition fusion methods. The experimental results show that these proposed multi-angle sclera recognition systems can achieve better performance in general. In addition, it shows that it is important to take system application needs into account when selecting the fusion method.
Keywords :
image classification; image fusion; iris recognition; human classification; human identification; image quality; image recognition; multiangle sclera recognition fusion method; multiangle sclera recognition system; sclera pattern; Accuracy; Databases; Image quality; Image recognition; Image segmentation; Iris recognition; Pattern matching; Multi-angle fusion-based sclera recognition; Quality measure; Sclera recognition;
Conference_Titel :
Computational Intelligence in Biometrics and Identity Management (CIBIM), 2011 IEEE Workshop on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9899-4
DOI :
10.1109/CIBIM.2011.5949225
