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PENGENALAN WAJAH DENGAN MENGIDENTIFIKASI MATA DAN HIDUNG MENGGUNAKAN METODE LOCAL BINARY PATTERN HISTOGRAM PADA MOBILE ROBOT

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Penilaian

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Face recognition is one of the technologies in Computer Vision that is widely used in recognizing someone. Face recognition uses facial pixel data in doing recognition. In this research, the reduction of the facial members used in making recognition, only uses the eyes and nose. In addition, data in facial recognition is also given a pixel width limit of 160 to 180 pixels. Through these reductions and restrictions, the accuracy and speed of the system in recognizing a person's face can be known. The Local Binary Pattern Histogram was chosen in this research because it is considered simpler, easier to understand and gives good results. In training and testing the data using the model provides accuracy and F1-Score of 69% and 56.7%, respectively with 200 training data and 50 testing data from 2 classes. Tests and applications on robots are also carried out in this research. The Mobile Robot was chosen in this research because it was considered to be able to fulfill the movement in scanning the target's face. In processing and processing image data, this research utilizes a mini computer, which is used to scan, face detection, eyes and nose identification, face recognition, send commands to the microcontroller, and so on. Microcontroller is also used to control the robot so that it can move to scan and follow faces. After the model is implanted and applied to the robot, it will perform scanning, detection, identification and facial recognition. At this raport, 20 samples were taken from the process and obtained accuracy and F1-Score of 90% and 88.8%, respectively. Also the facial recognition process is in time intervals of 0.30 to 0.40 seconds each time the image is processed (this process does not include detection, identification and movement of the robot).

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207005323	T84053	T840532022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T840532022

Publisher

Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xvii, 52 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem Pakar
Jurusan Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

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