TY - GEN
T1 - Biometric Recognition Based on Palm Vein Image Using Learning Vector Quantization
AU - Setiawan, Herry
AU - Yuniarno, Eko Mulyanto
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/11/15
Y1 - 2018/11/15
N2 - Every human being has its own uniqueness among humans that other good physical form or characteristic trait. Biometrics is the science that can recognize a part of an individual. Therefore, biometric identification is one of the ways that is done to identify the identity of the person. Palm vein biometric is one who lately attracted many researchers and industry because it has several advantages over other physical characteristics such as fingerprint, iris and face. Palm vein has internal features making it difficult undermined, modified and simulated with fake palms. In this study, design and implementation will do a recognition system through the venous vessels. Systems that were built capable of taking images of the Palm veins, detect the presence of venous vessels are then able to tell based on the database. This is done after the process of extraction, processing and manufacturing characteristics against the image of Palm vein vessels. The method used is the phase and learning vector quantization symmetri. Feature extraction using phase symmetri. phase symmetri applied by calculating the amplitude and phase of the signal frequency of the image of the vein which represents detailed information detailed variant of an image of the vein. While learning vector quantization is used for grouping the exclusive result of extraction. This research resulted in the classification with accuracy reaching 94%.
AB - Every human being has its own uniqueness among humans that other good physical form or characteristic trait. Biometrics is the science that can recognize a part of an individual. Therefore, biometric identification is one of the ways that is done to identify the identity of the person. Palm vein biometric is one who lately attracted many researchers and industry because it has several advantages over other physical characteristics such as fingerprint, iris and face. Palm vein has internal features making it difficult undermined, modified and simulated with fake palms. In this study, design and implementation will do a recognition system through the venous vessels. Systems that were built capable of taking images of the Palm veins, detect the presence of venous vessels are then able to tell based on the database. This is done after the process of extraction, processing and manufacturing characteristics against the image of Palm vein vessels. The method used is the phase and learning vector quantization symmetri. Feature extraction using phase symmetri. phase symmetri applied by calculating the amplitude and phase of the signal frequency of the image of the vein which represents detailed information detailed variant of an image of the vein. While learning vector quantization is used for grouping the exclusive result of extraction. This research resulted in the classification with accuracy reaching 94%.
KW - Biometric
KW - learning vector quantization
KW - palm vein
KW - pattern recognition
KW - phase symmetri
UR - http://www.scopus.com/inward/record.url?scp=85059363314&partnerID=8YFLogxK
U2 - 10.1109/ICICI-BME.2017.8537770
DO - 10.1109/ICICI-BME.2017.8537770
M3 - Conference contribution
AN - SCOPUS:85059363314
T3 - Proceedings of 2017 5th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering, ICICI-BME 2017
SP - 95
EP - 99
BT - Proceedings of 2017 5th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering, ICICI-BME 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering, ICICI-BME 2017
Y2 - 6 November 2017 through 7 November 2017
ER -