Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Grace Theresia Situmorang
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Metode Gray Level Cooccurence Matrix (GLCM) untuk Ekstraksi Ciri pada Telapak Tangan Grace Theresia Situmorang; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.926 KB)

Abstract

The increasing use of technology requires a security in the identification of individuals to avoid the access rights that can be known or compromised by others. One that can be utilized in maintaining information security required a science of biometrics. Biometrics is a natural human characteristic that is measurable and accurate, one of which, namely the palms became the object of this study is due to have unique characteristics of each individual whom the Palm's surface than with fingerprint pattern of the main lines, the pattern of tangled line/weak are stable. This can be combined with biometric extraction characteristics by using the various features. Extraction methods can be used namely Gray Level Cooccurence Matrix (GLCM) on the identification process by comparing the size and distance of the region of neighbornood. Beginning with the palm of the hand image capture a number of 208 image where 130 as a trainer and 78 data as test data. On the image of hands done pre-launch stage processing to change the color to grayscale image further divided into several sizes of the regions. The size of each region, performed the extraction phase characterized the Gray Level Cooccurence Matrix (GLCM) with a distance of neighbornood. This research get best accuracy percentage of 87.17% in the size of the region of 7 grids and the neighbornood distance d = 7.
Co-Authors Agus Wahyu Widodo Muh. Arif Rahman