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Biometrie systems face several limitations like low accuracy, less robustness, low applicability and non-universality which can be minimized by the adoption of Fusion at different levels of Biometric systems. Fusion can be applied at sensor level, features level, score level as well as decision level. In this paper, we have compared the performance of a Face Recognition system without fusion and with...
Identity management through biometrics provides huge advantage over traditional systems. This paper provides an extensive review of various biometrics technologies. A wide variety of biometric modalities like finger print, palm print, iris, facial features etc. are discussed in detail. Later these modalities are compared using various parameters. We have also discussed various multimodal biometric...
Some challenges of developing face recognition system is to train examples of different poses, illuminations, contrast and background conditions. Even though if the system works okay with the tested data set; it fails big time to perform accurately with new data set with different attributes. This manuscript is focusing on the mentioned problem statement by deploying PCA and implementing the concept...
In the last 57 years, face biometrie researchers have achieved many successes. Face recognition systems have been extensively used in government as well as commercial applications such as mobile, banking and surveillance systems etc. In the last 10 years, the whole biometric community such as researchers, developers, and retailers have worked on challenging tasks to develop a more accurate protection...
Facial expression recognition is a hot research direction of pattern recognition and computer vision. It has been increasingly used in artificial intelligence, human-computer interaction and security monitoring in recent years. Convolution neural network (CNN) as a depth learning architecture can extract the essential features of the image, and in the case of large changes in shooting conditions,...
Face recognition is an active and challenging task in pattern recognition and computer vision application. Sparse representation based classification has been verified to be powerful for face recognition. This paper proposes the metaface block sparse bayesian learning (MBSBL) based on the framework of sparse representation. The MBS-BL combines the metaface learning and block sparse bayesian learning...
A weighted version of fusion strategy is introduced for multiple biometrics that compensates the limitations impinged on single biometrics. The least intrusive facial biometrics that combines the facial behaviometrics for person identification is a new trend that needs further investigation. The aim of this study is to apply this weighted fusion scheme for our proposed bi-modal framework that uses...
Local binary pattern (LBP) has limitation in extracting the edge and direction information, which is vital to infrared face recognition. A new infrared face recognition algorithm fusion of LBP and histogram of oriented gradients (HOG) is proposed. First, LBP operator is adopted to extract the texture feature of an infrared face, and then the edge features of the original infrared face are extracted...
A practical method to improve the performance of off-line Handwritten Chinese Character Recognition (HCCR) was proposed in this paper. The center loss was used in face verification task to optimize intra-class distance. With the joint supervision of softmax loss and center loss, A light convolutional neural networks (CNNs) framework was trained for off-line HCCR which could optimize inter and intra...
Face recognition in real scenarios is mainly affected by illumination variation and occlusion, and therefore in order to develop a robust face recognition system these issues should be handled simultaneously. To this aim, the steps involved in the presented framework are (i) computationally simple and efficient preprocessing chain that eliminates major effects of illumination variation and noise while...
In this study, an SVM-based system is proposed for the classification of facial expressions that are represented in 3D. Distance based features are used as a feature vector, which are determined by the distances between the different key points on the image. Study was conducted on a subset (Happy, sadness, surprise) of Bosphorus 3D Face Database. 9 different fiducial points are used to calculate a...
Eye state recognition is still challenging in the field of computer vision. Many researchers have reported that their methods can work well with frontal face views, but not with variations of head poses. Some have described that their methods deal effectively with head pose problems, but the systems are complex to implement and consume a lot of processing time. In this paper, a novel method of eye...
Nowadays research has explored to extracting auxiliary information from various biometrie techniques such as fingerprints, face, iris, palm, voice etc. This information contains some features like gender, age, beard, mustache, scars, height, hair, skin color, glasses, weight, facial marks, tattoos etc. All this information contributes more and more to identification. The major changes that come across...
Humans are trying to interact with the computer via touch screen, smart-phones, audio and video. A computer get information from the human via an interface and likewise, a human recognize an information from the computer via an interface. Facial expression recognition is a key element in a human communication. In order to promote the man and machine interaction, a framework is proposed for the facial...
Planar spoofing is a well researched problem, wherein a high quality planar photograph can be replayed in front of a still camera as a substitute for another individual's face. Most modern day face recognition systems can be fooled by this process, as the perceptual information contained in a photo-of-a-photo, is virtually the same as that of a natural photograph of an individual. Current solutions...
Humans are capable to produce thousands of facial actions during communication that vary in intensity, complexity and meaning. The purpose of this paper is to recognize the human emotions in terms of happy, sad, surprise, neutral and disgust. Its aim is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database...
In digital image processing, orthogonal moments play an important role in image reconstruction, comparison and enhancement. Orthogonal Moments are derived from the polynomials which are mutually perpendicular and may be discrete or continuous. Most prominent continuous orthogonal moments include Legendre, Zernike and Pseudo-Zernike Moments and primary discrete orthogonal moments are Krawtchouk and...
Face recognition using sketches plays a major role in the field of forensic investigation and the field is considered to be more challenging domain for research work. The sketch forms a visual representation of a face and it can be utilized in many recognition applications for instance in facial expression recognition, retrieval of face, in the field of law enforcement and sketch-to-photo recognition...
This paper aims to experimental evaluation of different methodologies to recognize human face based on different facial expression. The face and facial images were captured locally, as the experiment is aimed to be done in India domain. The features were extracted based on two techniques, viz, Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The range of extracted feature is 150,300,600,1200...
In this paper, we propose a patch based semi-supervised linear regression (PSLR) approach to address single sample per person (SSPP) problem in face recognition, which takes full use of the unlabeled probe samples to learn facial variation information. We partition each face image into several overlapped patches, where each patch corresponds to a mapping matrix of regression model. Then, mapping matrix...
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