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The locations of the eyes are the most commonly used features to perform face normalisation (i.e. alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this study, the authors study the sensitivity of open source implementations of five face recognition algorithms to misalignment caused by eye localisation errors. They investigate the ambiguity...
The performance of an automated face recognition system can be significantly influenced by face image quality. Designing effective image quality index is necessary in order to provide real-time feedback for reducing the number of poor quality face images acquired during enrollment and authentication, thereby improving matching performance. In this study, the authors first evaluate techniques that...
Traditional approaches to face recognition have utilized aligned facial images containing both shape and texture information. This paper analyzes the contributions of the individual facial shape and texture components to face recognition. These two components are evaluated independently and we investigate methods to combine the information gained from each of them to enhance face recognition performance...
Many research teams have studied to make the blind see by stimulating the retina cells using electrical devices. But due to the limited number of electrodes, it needs to complement low resolution with image processing. In this paper, we tried to find the effect of image processing, especially with contrast enhancement (CE) technique. We investigated face recognition performance with three different...
Face recognition is an important task in the computer vision community leading to multiple applications such as building control access, video surveillance or forensics, to mention only a few. Face images are acquired in the enrollment process to form a database, which is the first stage usually performed off line. Second stage implies real-time test procedure where a new unseen face is captured and...
Recent studies show that face recognition in uncontrolled images remains a challenging problem, although the reasons why are less clear. Changes in illumination are one possible explanation, even though algorithms developed since the advent of the PIE and Yale B data bases supposedly compensate for illumination variation. Edge density has also been shown to be a strong predictor of algorithm failure...
Inspired by the superior performance of the dual-tree complex wavelet transform (DT-CWT) on signal representation and feature extraction, the well-known fisherface which is based on the linear discriminant analysis (LDA) and the eigenface which is based on the principal component analysis (PCA) are investigated in the DT-CWT domain and benchmarked in this paper. For the eigenface, the probabilistic...
Facial symmetry can be regarded as a not absolute but useful and natural feature. In this paper, this symmetrical feature is applied to two-dimensional linear discriminant analysis (2DLDA) for face image feature extraction, furthermore, the distance measure (DM) and Frobenius-norm measure(FM) are also developed to classify faces. Symmetrical 2DLDA (S2DLDA) used pure statistical mathematical technique...
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