A novel facial image recognition method based on perceptual hash using quintet triple binary pattern
Authors:
- Turker Tuncer,
- Sengul Dogan,
- Moloud Abdar,
- Paweł Pławiak
Abstract
Image classification (categorization) can be considered as one of the most breathtaking domains of contemporary research. Indeed, people cannot hide their faces and related lineaments since it is highly needed for daily communications. Therefore, face recognition is extensively used in biometric applications for security and personnel attendance control. In this study, a novel face recognition method based on perceptual hash is presented. The proposed perceptual hash is utilized for preprocessing and feature extraction phases. Discrete Wavelet Transform (DWT) and a novel graph based binary pattern, called quintet triple binary pattern (QTBP), are used. Meanwhile, the K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms are employed for classification task. The proposed face recognition method is tested on five well-known face datasets: AT&T, Face94, CIE, AR and LFW. Our proposed method achieved 100.0% classification accuracy for the AT&T, Face94 and CIE datasets, 99.4% for AR dataset and 97.1% classification accuracy for the LFW dataset. The time cost of the proposed method is O(nlogn). The obtained results and comparisons distinctly indicate that our proposed has a very good classification capability with short execution time.
- Record ID
- CUT84706a74dfd7426c8b1475799010f15b
- Publication categories
- ;
- Author
- Journal series
- Multimedia Tools and Applications, ISSN 1380-7501, e-ISSN 1573-7721
- Issue year
- 2020
- Vol
- 79
- No
- 39-40
- Pages
- 29573-29593
- Other elements of collation
- fot.; schem.; tab.; wykr.; Bibliografia (na s.) - 29590-29593; Bibliografia (liczba pozycji) - 87; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 79, Iss. 39-40
- Keywords in English
- face recognition, quintet triple binary pattern, perceptual hash, machine learning, biometrics
- DOI
- DOI:10.1007/s11042-020-09439-8 Opening in a new tab
- URL
- https://link.springer.com/article/10.1007%2Fs11042-020-09439-8 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 70
- Publication indicators
- Citation count
- 22
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT84706a74dfd7426c8b1475799010f15b/
- URN
urn:pkr-prod:CUT84706a74dfd7426c8b1475799010f15b
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.