This research presents an improved real-time face recognition system at a low resolution of 15 pixels with pose and emotion variations. We have designed our datasets named LRD200 LRD100, which been used for training classification. The detection part uses the Viola-Jones algorithm, receives image from to process it using Local Binary Pattern Histogram (LBPH) algorithm preprocessing contrast lim...

In this paper, a new Hidden Markov Model (HMM)-based face recognition system is proposed. As a novel point despite of five-state HMM used in pervious researches, we used 7-state HMM to cover more details. Indeed we add two new face regions, eyebrows and chin, to the model. As another novel point, we used a small number of quantized Singular Values Decomposition (SVD) coefficients as feature...

Despite recent advances in face recognition systems, they suffer from serious problems because of the extensive types of changes in human face (changes like light, glasses, head tilt, different emotional modes). Each one of these factors can significantly reduce the face recognition accuracy. Several methods have been proposed by researchers to overcome these problems. Nonetheless, in recent ye...

A novel discriminant analysis method is presented for the face recognition problem. It has been recently shown that the predictive objectives based on Parzen estimation are advantageous for learning discriminative projections if the class distributions are complicated in the projected space. However, the existing algorithms based on Parzen estimators require expensive computation to obtain the ...

Face recognition is one of biometric methods, to identify given face image using main features of face. In this paper, a neural based algorithm is presented, to detect frontal views of faces. The dimensionality of face image is reduced by the Kernel based 2 dimensional symmetrical principal component analysis (K2DSPCA) and the recognition is done by the Back propagation Neural Network (BPNN). H...

This paper describes a novel and adaptive dictionary method for face recognition using genetic algorithms (GAs) in determining the optimal basis for encoding human faces. In analogy to pursuit methods, our novel method is called Evolutionary Pursuit (EP), and it allows for diierent types of (non-orthogonal) bases. EP processes face images in a lower dimensional whitened PCA subspace. Directed b...

From 1970, research on automated face recognition has been on the rise. Since then many techniques and algorithms have been designed each one trying to provide better efficiency than the earlier one. This field of biometric analysis has found its use in many practical applications and with rising technologies each day, its exhaustive use in future is also expected. In this paper we have studied...

We tried to develop a real time face detection and recognition system which uses an "appearance-based" approach. For detection purpose we used Viola Jones algorithm. To recognize face we worked with Eigen Faces which is a PCA based algorithm. In a real time to recognize a face we need a data training set. For data training set we took five images of each person and manipulated the Eig...

In this paper we discuss some problem of Eigenfaces which is ignores in the previous work that is the question of which features are important for classification, and which are not. Eigenfaces seeks to answer this by using principal component analysis of the images of the faces. This analysis reduces the dimensionality of the training set, leaving only those features that are critical for face ...