DocumentCode :
3750092
Title :
Handwritten signature verification: Online verification using a fuzzy inference system
Author :
Md. Jahid Faruki;Ng Zhi Lun;Syed Khaleel Ahmed
Author_Institution :
Center for Signal Processing and Control Systems, Universiti Tenaga Nasional, Putrajaya Campus, Malaysia
fYear :
2015
Firstpage :
232
Lastpage :
237
Abstract :
Biometric features posses the significant advantage of being difficult to lose, forget or duplicate. Hence, a FIS-based method is used for signature verification. FIS is well suited for this task due to the similarity between an individual signatures with subtle differences between each signature sample. Signature samples are collected using a tablet PC. The individuals draw their signatures using a pressure sensitive pen on the tablet. Eight dynamic features are extracted from the signature data. These eight features are then fuzzified for training of a FIS. The system is then used to determine whether the signature is genuine or forged. A False Acceptance Rate (FAR) of 10.67% and a False Rejection Rate (FRR) of 8.0% demonstrate the promise of this system.
Keywords :
"Feature extraction","Training","Iris recognition","Data acquisition","Forgery","Testing"
Publisher :
ieee
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICSIPA.2015.7412195
Filename :
7412195
Link To Document :
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