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In this paper, we present an approach that unifies sub-space feature extraction and support vector classification for face recognition. Linear discriminant, independent component and principal component analyses are used for dimensionality reduction prior to introducing feature vectors to a support vector machine. The performance of the developed methods in(More)
Biometrics is the science and technology of measuring and analyzing biological data of human body for increasing systems security by providing accurate and reliable patterns and algorithms for person verification and identification and its solutions are widely used in governments, military and industries. Single source of information in biometric systems(More)
In large databases, creating user interfaces for browsing or performing insertion, deletion or modification of data is very costly in terms of programming. In addition, each modification of an access control policy causes many potential and unpredictable side effects which cause rule conflicts or security breaches that affect the corresponding user(More)
Template-Based face recognition methods have some limitation for the key points which are used for detection based on the common areas in facial images. One disadvantage of using a template-based method is that not all valuable key points are used. Nodes that are outside the areas that are sought with a template will be overlooked. Some of these key points(More)
This paper describes a new automated facial expression analysis system that integrates Locality Sensitive Hashing (LSH) with Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) to improve execution efficiency of emotion classification and continuous identification of unidentified facial expressions. Images are classified using(More)
Previous approaches to model and analyze facial expression analysis use three different techniques: facial action units, geometric features and graph based modelling. However, previous approaches have treated these technique separately. There is an interrelationship between these techniques. The facial expression analysis is significantly improved by(More)
To protect user's information, computer systems utilize access control models. These models are supported by a set of policies defined by security administrators in the environment where the organization is active. In previous studies it has been shown that building a user interface that dynamically changes with the security policies defined for each user(More)
Biometric data are the sensitive personal information and the large intra-class variability due to changes of the environment conditions is an issue in these type of data. Adaptive biometric is the solution that has been introduced and can make the systems more accurate and reliable. For this purpose, semi-supervised learning has been shown to be a possible(More)
In this paper, an approach based on self-organizing neural network with adaptive learning rate for color image segmentation is presented. It is well-known that the training speed depends on the choice of the learning rate. If the learning rate is small, the learning process is stable but at the expense of computation time. If the learning rate is too large,(More)