• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.20-30
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• 2003

In a conventional method based on quadrature 2D Gator 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 the ICA (Independent Component Analysis) 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 an individual's iris patterns. Additionally, we introduce two methods to enhance the recognition performance of the ICA. The first is to reorganize the ICA bases and the second is to use a different ICA bases set. Experimental results show that our proposed method has a similar EER (Equal Error Rate) as a conventional method based on the Gator wavelets, and the iris code size of our proposed methods is four times smaller than that of the Gabor wavelets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2424-2441
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• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.19-25
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• 2006

Iris recognition is a bio metric personal identification which uses iris pattern of the pupil, and it is recognized as one of the best technology in personal identification and information security field. Before iris recognition, it is very important to search center of pupil. In recent years, there was developed many searching algorithms of center of pupil, but all most method are too many processing time. In this paper, we proposed a new method for searching center of pupil. This method is greatly reduced processing time about 30% compared with other algorithm using Hough transformation.

• The Journal of Information Technology
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• v.12 no.4
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• pp.25-32
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. This paper is appropriate for the embedded environment using local gradient histogram embedded system using iris feature extraction methods have implement. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.227-230
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• 2002

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

• ETRI Journal
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• v.41 no.5
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• pp.599-607
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• 2019

Although iris recognition verification is considered to be the safest method of biometric verification, studies have shown that iris features may be illegally used. To protect iris features and further improve the security of iris recognition and verification, this study applies the Gaussian and Laplacian mechanisms and to hide iris features by differentiating privacy. The efficiency of the algorithm and evaluation of the image quality by the image hashing algorithm are selected as indicators to evaluate these mechanisms. The experimental results indicate that the security of an iris image can be significantly improved using differential privacy protection.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.31-40
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• 2012

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on Zernike Moment which is robust to rotations of iris patterns. we utilized a selection of Zernike moments for the fast and effective recognition by selecting global optimum moments and local optimum moments for optimal matching of each iris class. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.348-354
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• 2003

This proposes a new algorithm for advanced personal identification system using iris pattern and speech signal. Since the proposed algorithm adopts a fusion scheme to take advantage of iris recognition and speaker identification, it shows robustness for noisy environments. For evaluating the performance of the proposed scheme, we compare it with the iris pattern recognition and speaker identification respectively. In the experiments, the proposed method showed more 56.7% improvements than the iris recognition method and more 10% improvements than the speaker identification method for high quality security level. Also, in noisy environments, the proposed method showed more 30% improvements than the iris recognition method and more 60% improvements than the speaker identification method for high quality security level.

• Restorative Dentistry and Endodontics
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• v.29 no.2
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• pp.170-176
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• 2004

Objectives : In the unique metal iris method. the developing interfacial gap at the cavity floor resulting from the cavity wall property during polymerizing composite resin might affect the nominal shear bond strength values. The aim of this study is to evaluate that the iris method reduces the cohesive failure in the substrates and the cavity wall property effects on the shear bond strength tests using iris method. Materials and Methods : The occlusal dentin of 64 extracted human molars were randomly divided into 4 groups to simulate two different levels of cavity wall property (metal and dentin iris) and two different materials ($ONE-STEP^{\circledR}$ and $ALL-BOND^{\circledR}$ 2) for each wall property. After positioning the iris on the dentin surface. composite resin was packed and light-cured. After 24 hours the shear bond strength was measured at a crosshead speed of 0.5 mm/min. Fracture analysis was performed using a microscope and SEM. The data was analyzed statistically by a two-way ANOV A and t-test. Results : The shear bond strength with metal iris was significant higher than those with dentin iris (p＝0.034). Using $ONE-STEP^{\circledR}$, the shear bond strength with metal iris was significant higher than those with dentin iris (p＝0.005), but not in $ALL-BOND^{\circledR}$ 2 (p＝0.774). The incidence of cohesive failure was very lower than other shear bond strength tests that did not use iris method. Conclusions：The iris method may significantly reduce the cohesive failures in the substrates. According to the bonding agent systems. the shear bond strength was affected by the cavity wall property.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.6
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• pp.1538-1542
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• 2003

This Study was carried out for proof of confidence of Iris Diagnosis. We analyzed relation between Iris Signs and Chief Complain, and then analyzed relation between Iris Signs and Past History. The rate of relation between Iris Signs and Chief Complain was 72.1 %. The rate of relation between Iris Signs and Past History was 52.9%. synthetically, We had known that this diagnosis method have probability of 79.7%. It was confirmed that there are close correlations between Iris Signs and Chief Complain and between Iris Signs and Past History.