| 000 -LEADER |
|---|
| fixed length control field |
02780nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
FT8886 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20251217151545.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
251217b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9 A43 C37 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Carison, Ron Hale I.; Upaga, Chloe Gwyneth S. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
An enhancement of eigenface algorithm applied for identifying spoofing attacks in facial recognition |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Materials specified |
. |
| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Other physical details |
Undergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
|---|
| Source |
text |
| Content type term |
text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
unmediated |
| Media type term |
unmediated |
| Media type code |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
volume |
| Carrier type term |
volume |
| Carrier type code |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
ABSTRACT: The Eigenface Algorithm uses principal component analysis (PCA) to extract and represent facial features as eigenvectors for comparison with stored datasets. This is used for facial recognition that identifies individuals by extracting facial features and converting them into eigenvectors for comparison with stored datasets. However, it struggles with face occlusions, low-resolution images, and varying distances, affecting accuracy and increasing vulnerability to spoofing attacks. This research enhances the Eigenface Algorithm by integrating Super Resolution for improved facial feature extraction, LBPH for better occlusion and spoof detection, and a Distance-Based Scaling factor to optimize recognition within a 30 cm to 60 cm range. In this research, the researchers implemented OpenCV2 and stored the trained dataset in a YAML file. The dataset was generated by capturing multiple images across different environments and distances. The facial images were then preprocessed by resizing, converting to grayscale, incorporating Super-Resolution to enhance face image quality and applying LBPH for vector representation. Additionally, Distance Scaling was integrated to optimize facial recognition across varying distances. Results demonstrated improvements, with confidence levels reaching 90.79% and a substantial reduction in the error rate of 29.45%. The accuracy rate increased to 69.44%, while recognition time was remarkably decreased to just 0.0093 seconds. Additionally, the researchers recommend adapting the enhanced eigenface algorithm for other device types, 3D application and using larger dataset. These enhancements strengthen the algorithm’s resilience against spoofing attacks, augment its reliability in extracting intricate facial details amid noise, improve accuracy in recognizing occlusions and spoofed images, and enhance its usability in recognition attempts at unsuitable distances, thus enhancing usability in practical applications of facial recognition |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
|---|
| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Thesis/Dissertation |