2014
DOI: 10.3844/jcssp.2014.844.851
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Improved Real-Time Face Recognition Based on Three Level Wavelet Decomposition-Principal Component Analysis and Mahalanobis Distance

Abstract: The development of research in the field of real-time face recognition is a study that is being developed in the last decade. Face recognition is used to identify person from an image or video. Recognition rate and computation time of real-time face recognition is one of the big challenges that must be developed. This study proposes a model of face recognition using the method of feature extraction by combining three level wavelet decomposition and Principal Component Analysis (PCA) and using the method of mah… Show more

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Cited by 14 publications
(19 citation statements)
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“…Teknik pengenalan wajah secara garis besar dapat dibagi menjadi 3 kategori berdasarkan metodologi akuisisi data wajah [26], diantaranya: Metode yang beroperasi pada intensitas, lalu urutan dalam pengambilan gambar, informasi 3D atau citra infra merah. Pengenalan wajah ini, pada dasarnya digunakan untuk mengidentifikasi orang dari gambar atau video [27].…”
Section: B Landasan Teori 1) Pengenalan Wajah (Face Recognition)unclassified
“…Teknik pengenalan wajah secara garis besar dapat dibagi menjadi 3 kategori berdasarkan metodologi akuisisi data wajah [26], diantaranya: Metode yang beroperasi pada intensitas, lalu urutan dalam pengambilan gambar, informasi 3D atau citra infra merah. Pengenalan wajah ini, pada dasarnya digunakan untuk mengidentifikasi orang dari gambar atau video [27].…”
Section: B Landasan Teori 1) Pengenalan Wajah (Face Recognition)unclassified
“…As we are using the X-means to extracting the CLC set, the vectors descriptors do not have the same size for each model, so the Euclidean distance is not valid for our method. There are two distances that could adapt with our descriptors, the hausdorff distance and the Earth Mover Distance (EMD) (Rubner et al, 2000;Muruganathan et al, 2014;Edy et al, 2014). The EMD seems very expensive in terms of computation, then hausdorff distance is the most adaptable with the proposed vectors descriptors, also, it is the most used in this kind of problem.…”
Section: Similarity Measuringmentioning
confidence: 99%
“…Research on improving facial recognition was proposed by [9], who used a wavelet-PCA decomposition method with mahalanobis classification. The results of this study improved recognition by 95.7%.…”
Section: Related Workmentioning
confidence: 99%