RHENIA, TYA and Sutarno, Sutarno (2019) IDENTIFIKASI TANDA TANGAN MENGGUNAKAN EKSTRAKSI FITUR ZONING DAN EUCLIDEAN DISTANCE. Undergraduate thesis, Sriwijaya University.
Text
RAMA_56201_09011181419036.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) | Request a copy |
|
Preview |
Text
RAMA_56201_09011181419036_0201117802_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB) | Preview |
Text
RAMA_56201_09011181419036_0201117802_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (711kB) | Request a copy |
|
Text
RAMA_56201_09011181419036_0201117802_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (652kB) | Request a copy |
|
Text
RAMA_56201_09011181419036_0201117802_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy |
|
Text
RAMA_56201_09011181419036_0201117802_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (183kB) | Request a copy |
|
Text
RAMA_56201_09011181419036_0201117802_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (293kB) | Request a copy |
|
Text
RAMA_56201_09011181419036_0201117802_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy |
|
Text
RAMA_56201_09011181419036_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (8MB) | Request a copy |
Abstract
The signature is one of the biometrics owned by humans, one of the attributes most widely accepted as an identification system in recognizing someone. In this study, the author makes a system can help identify signatures in reality using a webcam. And add some results of the trial scenario. In this study the algorithm used is Euclidean Distance for recognition, and feature extraction using zoning. At the data training stage, the signature image must go through several stages of pre-processing processes such as grayscaling, thresholding, cropping, resizing, and extraction of zoning features. Then the new testing phase, using the calculation of the euclidean distance system will make decisions based on the proximity of the distance between the training data and test data. The results of system testing are those that can identify the owner of the signature. In this study used 140 samples of training data, 40 samples for non-realtime testing, and 20 samples for testing in realtime. The proposed system obtains an accuracy rate of 85% for non-realtime, and 70% for realtime results. To find out the accuracy of the algorithm used, the authors added several results of the test scenario, namely, the thickness of the pen, the light, the distance and the damaged image.
Item Type: | Thesis (Undergraduate) |
---|---|
Uncontrolled Keywords: | Identifikasi tanda tangan, zoning, euclidean distance |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science |
Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
Depositing User: | Users 1960 not found. |
Date Deposited: | 20 Sep 2019 07:52 |
Last Modified: | 20 Sep 2019 07:52 |
URI: | http://repository.unsri.ac.id/id/eprint/8178 |
Actions (login required)
View Item |