The recent development of deep learning-based generative models has sharply intensified the interest in data synthesis and its applications. Data synthesis takes on an added importance especially for some pattern recognition tasks in which some classes of data are rare and difficult to collect. In an iris dataset, for instance, the minority class samples include images of eyes with glasses, oversized or undersized pupils, misaligned iris locations, and iris occluded or contaminated by eyelids, eyelashes, or lighting reflections. Such class-imbalanced datasets often result in biased classification performance. Generative adversarial networks (GANs) are one of the most promising frameworks that learn to generate synthetic data through a two-player minimax game between a generator and a discriminator. In this paper, we utilized the state-of-the-art conditional Wasserstein generative adversarial network with gradient penalty (CWGAN-GP) for generating the minority class of iris images which saves huge amount of cost of human labors for rare data collection. With our model, the researcher can generate as many iris images of rare cases as they want and it helps to develop any deep learning algorithm whenever large size of dataset is needed.

We propose a 180-degree branch line coupler composed of two types of iris-loaded waveguides. The proposed coupler consists of two main transmission lines and branch lines with different electrical lengths. Based on optimal electrical lengths, a 180-degree output phase difference can be achieved without additional phase shifters. The two main lines with different electrical lengths are realized by capacitive and inductive iris-loaded waveguides. The size of the proposed coupler is nearly half that of the conventional 180-degree branch line coupler with additional phase shifters. Thus, the proposed coupler is of advantage with respect to the conventional one. We designed a proposed coupler in the K-band for satellite communication systems. The measurement results demonstrate a reflection of -20 dB, isolation of -20 dB, coupling response of -3.1+0.1 dB/-0.1 dB, and phase differences of 0+0.1 deg/-1.4 deg and -180+0.5 deg/-2.3 deg at a bandwidth of 8% in the K-band.

Biometric template protection techniques have been proposed to address security and privacy issues inherent to biometric-based authentication systems. However, it has been shown that the robustness of most of such techniques against reversibility and linkability attacks are overestimated. Thus, a thorough security analysis of recently proposed template protection schemes has to be carried out. Negative iris recognition is an interesting iris template protection scheme based on the concept of negative databases. In this paper, we present a comprehensive security analysis of this scheme in order to validate its practical usefulness. Although the authors of negative iris recognition claim that their scheme possesses both irreversibility and unlinkability, we demonstrate that more than 75% of the original iris-code bits can be recovered using a single protected template. Moreover, we show that the negative iris recognition scheme is vulnerable to attacks via record multiplicity where an adversary can combine several transformed templates to recover more proportion of the original iris-code. Finally, we demonstrate that the scheme does not possess unlinkability. The experimental results, on the CASIA-IrisV3 Interval public database, support our theory and confirm that the negative iris recognition scheme is susceptible to reversibility, linkability, and record multiplicity attacks.

Accurate segmentation of the region in the iris picture has a crucial influence on the reliability of the recognition system. In this letter, we present an end to end deep neural network based on U-Net. It uses dense connection blocks to replace the original convolutional layer, which can effectively improve the reuse rate of the feature layer. The proposed method takes U-net's skip connections to combine the same-scale feature maps from the upsampling phase and the downsampling phase in the upsampling process (merge layer). In the last layer of downsampling, it uses dilated convolution. The dilated convolution balances the iris region localization accuracy and the iris edge pixel prediction accuracy, further improving network performance. The experiments running on the Casia v4 Interval and IITD datasets, show that the proposed method improves segmentation performance.

In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.

Iris recognition is an important biometric method for personal identification. The accuracy of an iris recognition system highly depends on the success of an iris segmentation step. In this paper, a robust and accurate iris segmentation algorithm for closed-up NIR eye images is developed. The proposed method addressed problems of different characteristics of iris databases using local image properties. A precise pupil boundary is located with an adaptive thresholding combined with a gradient-based refinement approach. A new criteria, called a local signal-to-noise ratio (LSNR) of an edge map of an eye image is proposed for localization of the iris's outer boundary. The boundary is modeled with a weighted circular integral of LSNR optimization technique. The proposed method is experimented with multiple iris databases. The obtained results demonstrated that the proposed iris segmentation method is robust and desirable. The proposed method accurately segments iris region, excluding eyelids, eyelashes and light reflections against multiple iris databases without parameter tunings. The proposed iris segmentation method reduced false negative rate of the iris recognition system by half, compared to results obtained using Masek's method.

Despite their usability advantages over traditional authentication systems, biometrics-based authentication systems suffer from inherent privacy violation and non-revocability issues. In order to address these issues, the concept of cancelable biometrics was introduced as a means of generating multiple, revocable, and noninvertible identities from true biometric templates. Apart from BioHashing, which is a two-factor cancelable biometrics technique based on mixing a set of tokenized user-specific random numbers with biometric features, cancelable biometrics techniques usually cannot preserve the recognition accuracy achieved using the unprotected biometric systems. However, as the employed token can be lost, shared, or stolen, BioHashing suffers from the same issues associated with token-based authentication systems. In this paper, a reliable tokenless cancelable biometrics scheme, referred to as BioEncoding, for protecting IrisCodes is presented. Unlike BioHashing, BioEncoding can be used as a one-factor authentication scheme that relies only on sole IrisCodes. A unique noninvertible compact bit-string, referred to as BioCode, is randomly derived from a true IrisCode. Rather than the true IrisCode, the derived BioCode can be used efficiently to verify the user identity without degrading the recognition accuracy obtained using original IrisCodes. Additionally, BioEncoding satisfies all the requirements of the cancelable biometrics construct. The performance of BioEncoding is compared with the performance of BioHashing in the stolen-token scenario and the experimental results show the superiority of the proposed method over BioHashing-based techniques.

We previously proposed a rotation-spreading neural network (R-SAN net). This neural net can recognize the orientation of an object irrespective of its shape, and its shape irrespective of its orientation. The R-SAN net is suitable for orientation recognition of a concentric circular pattern such as an iris image. Previously, variations of ambient lighting conditions affected iris detection. In this study, we introduce brightness normalization for accuracy improvement of iris detection in various lighting conditions. Brightness normalization provides high accuracy iris extraction in severe lighting conditions. A recognition experiment investigated the characteristics of rotation and shape recognition for both learned and un-learned iris images in various plane rotations. The R-SAN net recognized the rotation angle for the learned iris images in arbitrary orientation, but not for un-learned iris images. Thus, the variation of the rotation angle was corrected only for learned irises, but not un-learned irises. Although the R-SAN net rightly recognized the learned irises, it could not completely reject the un-learned irises as unregistered irises. Using the specific orientation recognition characteristics of the R-SAN net, a minimum distance was introduced as a new shape recognition criterion for the R-SAN net. In consequence, the R-SAN net combined with the minimum distance rightly recognized both learned (registered) and un-learned irises; the unregistered irises were correctly rejected.

In a conventional method based on quadrature 2D Gabor wavelets to extract iris features, the iris recognition is performed by a 256-byte iris code, which is computed by applying the Gabor wavelets to a given area of the iris. However, there is a code redundancy because the iris code is generated by basis functions without considering the characteristics of the iris texture. Therefore, the size of the iris code is increased unnecessarily. In this paper we propose a new feature extraction algorithm based on independent component analysis (ICA) for a compact iris code. We implemented the ICA to generate optimal basis functions which could represent iris signals efficiently. In practice the coefficients of the ICA expansions are used as feature vectors. Then iris feature vectors are encoded into the iris code for storing and comparing individual's iris patterns. Additionally, we introduce a method to refine the ICA basis functions for improving the recognition performance. Experimental results show that our proposed method has a similar equal error rate as a conventional method based on the Gabor wavelets, and the iris code size of our proposed methods is five times smaller than that of the Gabor wavelets.

Iris recognition is to identify a user based on the iris texture information which exists between the white sclera and the black pupil. Iris recognition system has been in the limelight for high-security biometric applications due to the advantages of non-contact characteristics and the highest recognition performance among biometric systems. Conventional iris recognition systems consist of the iris camera and the processing unit, like a PC or an embedded control box. The iris camera captures the user's iris images and transfers them to the processing unit. In the processing unit, the captured images are processed and recognition is performed. For fast recognition, it is very important to capture the user's focused eye image at fast speed. If not, the total recognition time is increased and it makes the user feel much inconvenience. In previous researches and systems, they use the focusing method which has been used for general landscape scenes without considering the characteristics of iris image. So, they take much focusing time sometimes, especially in the case of the user with glasses. To overcome such a problem, we propose a new iris image acquisition method to capture the user's focused eye image at very fast speed. It can be applicable to the users both with and without glasses.

In this paper, we propose a transformation function for a user's raw iris data, an "iris code" in iris scanning verification on the server, since the iris code requires to be hidden from even a server administrator. We then show that the user can be properly authenticated on the server, even though the iris code is transformed by the proposed function. The reason is that the function has a characteristic, "The (normalized) Hamming distances between the enrolled iris codes and the verified iris codes are conserved before and after the computation of the function," that is, the normalized Hamming distance in this scheme is equal to that in the existing scheme. We also show that the transformed iris code is sufficiently secure to hide the original iris code, even if a stronger attack model is supposed than the previously described model. That can be explained from the following two reasons. One reason is that nonlinear function, which consists of the three-dimensional rotation about the x-axis and the y-axis with the iris code lengthened bit by bit, and the cyclic shift, does not enable an attacker to conjecture the iris code. The other reason is that the success probabilities for the exhaustive search attack concerning the iris code in the supposed attack models are lower than those of the previously proposed methods and are negligible.

In this paper, we introduce a new technology to extract the unique features from an iris image, which uses scale-space filtering. Resulting iris code can be used to develop a system for rapid and automatic human identification with high reliability and confidence levels. First, an iris part is separated from the whole image and the radius and center of the iris are evaluated. Next, the regions that have a high possibility of being noise are discriminated and the features presented in the highly detailed pattern are then extracted. In order to conserve the original signal while minimizing the effect of noise, scale-space filtering is applied. Experiments are performed using a set of 272 iris images taken from 18 persons. Test results show that the iris feature patterns of different persons are clearly discriminated from those of the same person.

Iris recognition is used to identify a user based on the iris texture information which exists between the white sclera and the black pupil. For fast iris recognition, it is very important to capture user's focused eye image at fast speed. If not, the total recognition time is increased and it makes the user feel much inconvenience. In previous researches and systems, they use the focusing method which has been used for general landscape scene without considering the characteristics of iris image. So, they take much focusing time sometimes, especially in case of the user with glasses. To overcome such problems, we propose a new iris image acquisition method to capture user's focused eye image at very fast speed based on the corneal specular reflection. Experimental results show that the focusing time for both the users with glasses and without glasses is average 480 ms and we can conclude our method can be used for the real-time iris recognition camera.

An approximate formula is proposed for the equivalent susceptance of a circular iris in a parallel plate waveguide when the TEM mode cylindrical wave is incident from the center of the iris. Schwinger's variational method for a linear iris is generalized to the cylindrical case, and an approximate closed form formula is obtained which recovers the result of the linear iris when the radius of the circular iris is sufficiently larger than the wavelength. For verification of the formula, an exact integral equation is formulated and solved numerically by Galerkin's method. A comparison between them shows good agreement.

This paper shows an analysis of electromagnetic scattering from an open-ended rectangular cylinder for a plane wave incidence. The internal region is separated into two areas by additional plates to investigate the cavity resonance in detail. The applied numerical technique is the point matching method taking account of the edge condition. As numerical examples, the radar cross section is presented for E - polarized case and H - polarized case. Physical meanings of the computational results are discussed with a view to the contribution of the iris.

The problem of electromagnetic scattering caused by inductive discontinuities locate in parallel-plate waveguides, in particular when dealing with discontinuous conductors of finite thickness, is analyzed using the modified residue-calculus method, the equations suitable for a numerical calculation are derived. The incident wave is taken to be the dominant mode, and the reflection and transmission properties of a symmetrical inductive iris are discussed.

The problem of electromagnetic scattering by capacitive discontinuities located in rectangular waveguides, in particular when dealing with discontinuous conductors of finite thickness, is analyzed using the modified residue-calculus method, and form of the equation suitable for a numerical calculation is derived. The incident wave is taken to be the dominant mode, and reflection and transmission properties of an asymmetric capacitive iris are discussed. After the modal representation of the filed, the modal matching is apply to satisfy the boundary conditions at the discontinuity. And using the modified residue-calculus method, simultaneous infinite equations, which are concerned with the scattered mode coefficients, are derived. Then they are approximated at the thick diaphragm. The solutions obtained take on the form of an infinite product, and a numerical solution based on the method of successive approximations is presented as a technique for concretely determining the reflection coefficients. As confirmation, experiments are also carried out in the X-band and close agreement is shown between the calculated and experimental values.

The precise phase characteristics of the reflected and transmitted waves are obtained for electromagnetic scattering by inductive discontinuities of finite thickness located in rectangular waveguides. The incident wave is assumed to be the dominant mode, and the modified residue-calculus method is used for numerical analysis. The phase characteristics when the thickness and width of the iris are varied, and characteristics of the reflected and transmitted waves when resonance appears, are discussed. In addition, an X-band experiment is performed and the calculations for both the reflected and transmitted waves are shown to agree well with the experimental values.

The problem of electromagnetic scattering by inductive discontinuities located in rectangular waveguides, in particular when dealing with discontinuous conductors of finite thickness, is analyzed using the modified residue-calculus method, and form of the equation suitable for a numerical calculation is derived. The incident wave is taken to be the dominant mode, and reflection and transmission properties of an asymmetric inductive iris are discussed. After the modal representation of the filed, the modal matching is apply to satisfy the boundary conditions at the discontinuity. And using the modified residue-calculus method, simultaneous infinite equations, which are concerned with the scattered mode coefficients, are derived. Then they are approximated at the thick diaphragm. The solutions obtained take on the form of an infinite product, and a numerical solution based on the method of successive approximations is presented as a technique for concretely determining the reflection coefficients. As confirmation, experiments are also carried out in the X-band and close agreement is shown between the calculated and experimental values.