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Content Provider | IET Digital Library |
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Author | Turhan, Ceren Guzel Bilge, Hasan Sakir |
Abstract | Interests in biometric identification systems have led to many face recognition task-oriented studies. These studies often address the detection of face images taken from a camera and the recognition of faces via extracted meaningful features. To meet the requirement of defining data with fewer features, principal component analysis (PCA)-based techniques are widely used due to their efficiency and simplicity. There is a remarkable interest in the used efficiency of PCA by extending this traditional technique with various aspects. From this viewpoint, this study is specifically focused on the PCA-based face recognition techniques. By enhancing the methods in the reviewed studies, a novel class-wise two-dimensional PCA-based face recognition algorithm is presented in this study. Unlike the traditional method, this method generates more than one subspace considering within-class scattering. A system based on the presented approach can successively detect and recognise faces in not only images but also in video files. In addition, analyses were conducted to evaluate the efficiency of the proposed algorithm and its extension comparing with other addressed PCA-based methods. On the basis of the experimental results, it is clear to say that the presented approach and its extension are superior to the compared PCA-based algorithms. |
Starting Page | 286 |
Ending Page | 300 |
Page Count | 15 |
ISSN | 17519632 |
Volume Number | 11 |
e-ISSN | 17519640 |
Issue Number | Issue 4, Jun (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cvi/11/4 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0135 |
Journal | IET Computer Vision |
Publisher Date | 2016-09-11 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Biometric Identification System Class-wise 2D PCA Method Computer Vision And Image Processing Technique Face Image Detection Face Recognition Feature Extraction Image Recognition Image Sonsor Meaningful Feature Extraction PCA-based Face Recognition Technique Principal Component Analysis Statistics Video Files Video Signal Processing |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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