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Deformation of iris pattern caused by pupil dilation and contraction is one of the most influential intra-class variations. Most state-of-the-art iris recognition methods only focus on the description of local iris texture features. We believe that both geometric and photometric features are important to achieve a robust matching result of deformed iris images. This paper proposes to decompose iris...
This paper explores an efficient algorithm for iris recognition based on Hierarchical Phase-Based Image Matching (HPM) technique. One of the difficult problems in feature-based iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of image acquisition. The proposed system is...
Biometrics has become more and more important in security applications. In comparison with many other biometrie features, iris recognition has very high recognition accuracy. Successful iris recognition matching depends on how similar the stored template in database is compared with the introduced template. The main objective of this paper is to introduce a high performance scheme for iris recognition...
This paper proposes a novel approach for feature extraction using bit plane slicing. This technique is preferred over some traditional methods of feature extraction using orthogonal and non orthogonal transforms that uses real features. The extracted real features are computationally expensive in terms of time and storage. The proposed iris based biometric system is implemented by localizing the inner...
Currently there is an increasing demand for human-recognition systems using Iris as a pattern for representing a person's identity. A typical Iris recognition system is composed of four steps: image acquisition, iris segmentation, feature extraction and matching. This paper focuses on the matching step. Particularly, it is proposed a new method of iris matching, the Novelty Filter, tailored to compare...
This paper presents an efficient IrisCode classifier, built from phase features which uses AdaBoost for the selection of Gabor wavelets bandwidths. The final iris classifier consists of a weighted contribution of weak classifiers. As weak classifiers we use 3-split decision trees that identify a candidate based on the Levenshtein distance between phase vectors of the respective iris images. Our experiments...
Traditional iris recognition systems can achieve excellent performance in both verification and identification. However, most of the existing systems adopted a similar technique to deal with the iris image. In this paper, we propose a novel matching strategy with invariant properties, which is based on the possibilistic fuzzy clustering algorithm, to compare a pair of local feature sets. Moreover,...
The goal of this paper is to analyze the texture of irides and determine if they can be quantitatively measured and assigned into multiple categories. Such an exercise would ensure that irides, like fingerprints, can be partitioned into multiple classes thereby allowing for faster retrieval of identities in large scale biometric systems. In order to facilitate this, a set of 68 statistical features...
This paper proposes a method to segment iris area from the closed-up eye image. The method is a model-based method. It approximates pupil boundary and iris boundary using two circles, and approximates eyelids using two parabolas. The proposed method utilizes intensity gradient with local refinement to detect pupil boundary. A new concept of using signal to noise ratio (SNR), a ratio of mean and standard...
Understanding people attentional focus can be useful for several applications. One important challenge in this area is to determine the iris position in image/video in order to estimate gaze behavior. To this end, this paper presents a robust and non-intrusive method to locate human iris position in low resolution grayscale images, in real-time. The method requires the previous knowledge of the face...
Current iris recognition systems usually regard poor quality iris images useless since defocused or partially occluded iris images may cause false acceptance. However, such a strategy may lose an opportunity to correctly report a genuine match with poor-quality samples. This paper proposes an adaptive iris matching method to improve the throughput of iris recognition systems. The core idea of the...
In recent times the security has become a major issue of concern among the people. There is multifold increase in the installation and deployment of security services around the world. The threat starts when an unwanted person tries to obtain access to any place or value. In such a scenario the correct identification of the person is necessary so as to restrict the unidentified people from gaining...
This paper introduces an eye-verifier for reliable detection of eyes in facial color images. At first, the eye region candidates are searched by the circular filter to the binary face image. The eye candidates are then fed into an eye-verifier. The eye-verifier uses a ternary template, generated from the eye area consisting of iris, sclera and skin. Then the template matching is made by ternary Hamming...
Biometrics is an effective technology for personnel identity authentication (PIA), but unimodal biometric systems which use a single trait for authentication, will suffer from problems like noisy sensor data, nonuniversality, lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. These problems can be tackled by using multi-biometrics in the system. This paper...
This paper proposes a novel feature extraction and matching technique for iris recognition using interest points. The feature set comprises of spatial location of corner points and entropy information of the window around the corner. Corner matching is an elementary problem that is resolved using dual stage approach. At first stage the potential corners are obtained by finding Euclidean distance between...
The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors, subjective factors and variable factors. We adopt different strategies to compute the corresponding...
A person only has two irises - if his pattern is stolen he quickly runs out of alternatives. Thus methods that protect the true iris pattern need to be adopted in practical biometric applications. In particular, it is desirable to have a system that can generate a new unique pattern if the one being used is lost, or generate different unique patterns for different applications to prevent cross-matching...
In this paper, a new efficient feature matching method for a very large iris database is proposed. The new method is particularly useful for the iris recognition system that works with the popular IrisCode features. The method initially performs a partial feature matching between segments of IrisCodes after random permutation. This partial matching results in a reduced set of candidate IrisCodes on...
This paper investigates the differences between fractal encoding and other existing image enhancement techniques, such as bicubic interpolation, for iris image enhancement and their performance benefits when matching iris images from the ICE database. The algorithm used for iris recognition is the freely available Libor Masek Matlab code. Commercially available software was used for fractal encoding.
This paper focuses on the rotation noise of iris recognition. Current iris recognition systems are unable to deal with the rotation noise perfectly. We propose a novel method for iris matching that decompose iris picture into wavelet subband coefficients via 16 non-separable wavelet filters, and use generalized Gaussian density (GGD) modeling of each non-separable orthogonal wavelet coefficients as...
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