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 mahalanobis distance for the classification section (3WPCA-MD). A 3-level wavelet decomposition is used to decompose images by reducing the resolution used for those images. Using wavelet decomposition up to level 3 will produce an image with a very low resolution so as to reduce the value of the resulting computation time to be processed using PCA. Mahalanobis distance method is used to determine the degree of similarity among the features to produce a more optimal face recognition. Based on the results of experiments that have been done, they generated improved face recognition with high face recognition accuracy of up to 96% in average and produced faster computation results of face recognition if compared to ordinary PCA method. The average computation speed value obtained using the method of 3WPCA-MD was 5-7 milli-second (ms) for each face recognition process.
Highlights
Facerecognition system is an application of computer technology to make detection and face reconstruction (Jafri and Arabnia, 2009)
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 mahalanobis distance for the classification section (3WPCA-MD)
Face recognition the methodology of data acquisition, face recognition system is a way to recognize human faces of both still is divided into 3 categories: Face recognition method images and moving images such as real-time videos based on image intensity; face recognition method that taken from a camera or webcam
Summary
Image database investigations, “smart card” applications, multi-media environments, video indexing and witness. Facerecognition system is an application of computer technology to make detection and face reconstruction (Jafri and Arabnia, 2009). According to Jafri and Arabnia (2009), based on recognition of detected human faces. Face recognition the methodology of data acquisition, face recognition system is a way to recognize human faces of both still is divided into 3 categories: Face recognition method images and moving images such as real-time videos based on image intensity; face recognition method that taken from a camera or webcam. Face detection uses algorithm that is able to classify human works based on video sequences and face recognition method that requires other sensors such as 3D faces and recognize the identity of the detected faces. The method of face recognition system has been information and infrared imagery.
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