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Darma Putra
Udayana University
Computer Science & IT

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Time Series Based for Online Signature Verification Pande Sutawan; Darma Putra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 4: December 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i4.1186

Abstract

Signature verification system is to match the tested signature with a claimed signature. This paper propose time series based for feature extraction method and dynamic time warping for match method. The system made by process of testing 900 signatures belong to 50 participants, 3 signatures for reference and 5 signatures from original user, simple imposters and trained imposters for signatures test. The final result system was tested with 50 participants with 3 references. This test obtained that system accuracy without imposters is 90,45 % at threshold 44 with rejection errors (FNMR) is 5,2% and acceptance errors (FMR) is 4,35 %, when with imposters system accuracy is 80,13 % at threshold 27 with error rejection (FNMR) is 15,6% and acceptance errors (average FMR) is 4,26 %, with details as follows: acceptance errors is 0,39%, acceptance errors simple imposters is 3,2% and acceptance errors trained imposters is 9,2%.
Palmprint Verification Using Time Series Method Agus Anwar; Darma Putra; Agung Cahyawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 4: December 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i4.1187

Abstract

The use of biometrics as an automatic recognition system is growing rapidly in solving security problems; palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI) segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palm print. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036).
Palmprint Verification Using Time Series Method Agus Anwar; Darma Putra; Agung Cahyawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 4: December 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i4.1188

Abstract

The use of biometrics as an automatic recognition system is growing rapidly in solving security problems; palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI) segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palm print. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036).
Co-Authors Agus Anwar Anak Agung Ketut Agung Cahyawan Wiranatha Pande Sutawan