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In this paper, we propose a light version (LV) algorithm that can recognize iris images in smartphones. The contribution is threefold. Firstly, we modified and re-designed the iris recognition algorithm that is capable of working in smartphone environment. Secondly, the modified algorithm is then extended in such a way that the best optimized solution can be found for authentication or verification...
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...
This paper describes an automatic approach for iris segmentation and recognition with focus on twins. The technique entails localizing and segmenting the iris, followed by iris normalization and obtaining distinctive features. Lastly, iris templates are matched to realize one to one and one to many recognition in twins. Further, effect of various template sizes on the accuracy and memory requirement...
The periocular region has recently emerged as a standalone biometric trait, promising attractive tradeoff between the iris alone and the entire face, especially for cases where neither the iris nor a full facial image can be acquired. This advantage provides another dimension for implementing a robust biometric system performed in non-ideal conditions. Global features [local binary pattern (LBP),...
Iris is one of the popular biometrics that is widely used for identity authentication. Different features have been used to perform iris recognition in the past. Most of them are based on hand-crafted features designed by biometrics experts. Due to tremendous success of deep learning in computer vision problems, there has been a lot of interest in applying features learned by convolutional neural...
Recently, Gait recognition has gained significant attention. It is the identification of individuals in a video sequences, the recognition method is by the way they walk. Active Energy Image (AEI) is a more efficient represent method than Gait Energy Image (GEI), Gabor wavelet is used in face recognition successfully, so we use the Gabor wavelet to extract the amplitude spectral of AEI, research the...
This paper presents a novel human ear recognition approach based on Multi-scale Local Binary Pattern (MLBP) descriptor to enhance the recognition performance. The proposed method includes the following two steps: (i) the feature extraction step that computes the MLBP descriptor-based features from human ear images, and (ii) the matching process that uses the Kullback Leibler (KL) distance to capture...
A human brain can store and remember thousands of faces in a person's life time, however it is very difficult for an automated system to reproduce the same results. Faces are complex and multidimensional which makes extraction of facial features to be very challenging, yet it is imperative for our face recognition systems to be better than our brain's capabilities. The face like many physiological...
Periocular recognition promises attractive trade-off between iris recognition and face recognition because it provides a longer range of imaging than iris and could achieve a higher recognition performance than face. This benefit is critical to the success of a biometric system under unconstrained and less cooperative operating conditions. A number of feature encoding techniques have been proposed...
Previous work on iris recognition focused on either Visible Light (VL), Near-Infrared (NIR) imaging or the fusion between them. However, limited numbers of works have compared the iris biometric performance under both VL and NIR spectrum using images taken from the same subject. In this paper, we explore the differences in iris recognition performance across the VL and NIR spectrum. In addition, we...
Human Robot Interaction is a multidisciplinary field which involves developing, perceiving and assessing robotic systems. In effective communication, the understanding of emotions and intentions are essential. A robotic system that is capable of recognizing emotion states and synthesizing proper response would be beneficial for Human Robot Interaction (HRI). Human emotion recognition could be achieved...
This study presents a multimodal system that optimises and integrates the iris and face features based on fusion at the score level. The proposed multibiometric system has two novelties as compared with the previous work. First, the authors deploy a fuzzy C-means clustering with level set (FCMLS) method in an effort to localise the non-ideal iris images accurately. The FCMLS method incorporates the...
It is presented a novel pupillary-based identification system, along with the early identity authentication results and analysis, based on the spatio-temporal features computed from the spontaneous pupillary oscillations. The authors demonstrate that this biometric trait has the capability to provide enough discriminative information to authenticate the identity of a subject. A new methodology to...
This paper presents a survey on sclera-based biometric recognition. Among the various biometric methods, sclera is one of the novel and promising biometric techniques. The sclera, a white region of connective tissue and blood vessels, surrounds the iris. A survey of the techniques available in the area of sclera biometrics will be of great assistance to researchers, and hence a comprehensive effort...
It is normal that the distance between palm and camera lens is different in contactless recognition systems. Most of the prior work has only emphasized on issues of preprocessing, feature extraction and match. But the recognition affect due to the different distance of image is very few concerned. This paper presents the relationship between palm distance and the palmvein recognition performance from...
The purpose of the work presented in this paper is to adapt the feature extraction and matching steps of iris recognition to the quality of the input images. To this end we define a GMM-based global quality metric associated to a pair of normalized iris images. It quantifies the amount of artifact in these images as well as the amount of texture in artifact-free regions. First we use this metric to...
Human identification based on iris biometrics requires high resolution iris images of a cooperative subject. Such images cannot be obtained in non-intrusive applications such as surveillance. However, the full region around the eye, known as the periocular region, can be acquired non-intrusively and used as a biometric. In this paper we investigate the use of periocular region for person identification...
Multimodal eye recognition can improve the biometric systems recognition accuracy by combining iris and sclera recognition. However, poor quality images can significantly affect the system performance. In this paper, we proposed a quality fusion based multimodal eye recognition. Our quality measure evaluated the entire eye image quality, iris area quality, and sclera area quality. The experimental...
In recent years, the drowsiness recognition is widely applied to the driver alerting or distance learning. The drowsiness recognition system is constructed on the basis of the recognition of eye states. The conventional methods for recognizing the eye states are often influenced by the illumination variations or hair/glasses occlusion. In this paper, we propose a new image feature called ¡§least correlated...
In this paper, a low complexity technique is proposed for iris recognition in the curvelet transform domain. The proposed method does not require the detection of outer boundary and decreases unwanted artefacts such as the eyelid and eyelash. Thus, the time required for preprocessing of an iris image is significantly reduced. The zero-crossings of the transform coefficients are used to generate the...
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