Palm recognition using local binary pattern histogram and cascade method

The use of palms in the self-recognition process can be difficult to fake and tends to be stable because it has unique characteristics. Because of the unique characteristics of the palms, they can be used as a means of verifying a person’s identity by matching the data contained in the database with...

Full description

Saved in:
Bibliographic Details
Main Authors: Pangesti, Witriana E., Azizah, Qudsiah N., Pratama, Eva A., Suriyanto, Adhi D., Andreyestha
Format: Conference Proceeding
Language:English
Subjects:
Data retrieval
Histograms
Uniqueness
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The use of palms in the self-recognition process can be difficult to fake and tends to be stable because it has unique characteristics. Because of the unique characteristics of the palms, they can be used as a means of verifying a person’s identity by matching the data contained in the database with the data entered. This research was conducted to detect palms. Which later is expected to help facilitate the work in handling palm detection. So that further actions can be taken to verify a person’s identity. In the image data retrieval process with a total of 200 palm image files. Which consists of 2 people with 100 images of their palms each. Based on the results of trials conducted using the Cascade Classifier and Local Binary Pattern Histogram (LBPH) method, the accuracy of palm detection or identification percentage is quite high, namely 90
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0128575