TY - GEN
T1 - A study on multi-unit iris recognition
AU - Jang, Jain
AU - Park, Kang Ryoung
AU - Son, Jinho
AU - Lee, Yillbyung
PY - 2004
Y1 - 2004
N2 - Iris recognition system has achieved good performance, but it is affected by the quality of input data. In this paper, we propose a multi-unit iris recognition system, which can select the good quality data between multi-unit eye images of the same person. The system is composed of four stages. First, both iris data are captured at the same time. After that the eye image check algorithm rejects noisy and counterfeit data. At the third stage, features are extracted by Daubechies' Wavelet. Finally, features are classified by Support Vector Machines (SVM) and Euclidian distance. We select the better accuracy rate between results of two methods. Experiment results involve 1694 eye images of 111 different people and the best accuracy rate is 99.1%.
AB - Iris recognition system has achieved good performance, but it is affected by the quality of input data. In this paper, we propose a multi-unit iris recognition system, which can select the good quality data between multi-unit eye images of the same person. The system is composed of four stages. First, both iris data are captured at the same time. After that the eye image check algorithm rejects noisy and counterfeit data. At the third stage, features are extracted by Daubechies' Wavelet. Finally, features are classified by Support Vector Machines (SVM) and Euclidian distance. We select the better accuracy rate between results of two methods. Experiment results involve 1694 eye images of 111 different people and the best accuracy rate is 99.1%.
UR - http://www.scopus.com/inward/record.url?scp=21244487116&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:21244487116
SN - 0780386531
T3 - 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
SP - 1244
EP - 1249
BT - 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
T2 - 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Y2 - 6 December 2004 through 9 December 2004
ER -