Open AccessVerifikasi Tanda Tangan Menggunakan Ekstraksi Fitur LBP dan Klasifikasi LVQ
Author(s) -
Medeline Widia Andani,
Fitri Bimantoro
Publication year - 2020
Publication title -
jurnal teknologi informasi, komputer dan aplikasinya
Language(s) - English
Resource type - Journals
ISSN - 2657-0327
DOI - 10.29303/jtika.v2i2.107
Subject(s) - learning vector quantization , computer science , artificial intelligence , pattern recognition (psychology) , local binary patterns , vector quantization , histogram , image (mathematics)
Signature is one of the media used for verification and legalization of information, such as documents that are closely related to legality. In general, signature verification is done manually by direct comparing, this is certainly not effective, especially if doing a lot verification. Therefore, we need a computer system that can automatically verify a person's signature to save time in matching and reducing errors. This research was conducted using feature of Local Binary Pattern (LBP) method and Learning Vector Quantization (LVQ) classifier. Materials that used in this research are 600 signature images with a size of 500x500 pixels taken from 30 respondents where each respondent taken 15 original signatures and 5 fake signatures. The results of this research are that the signature identification process resulted in 93% and the verification process resulted in an accuracy of 63%, a sensitivity of 89%, and a specificity of 42%.