• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.318-321
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• 2001

We have designed an Internet voting system applicable for worldwide voting which is based on Ohkubo et. al,'s scheme[9] combined with Public Key Infrastructure (PKI). To the best of our knowledge, this is the first trial to serve secure Internet voting system to the world. In our system, voter's privacy is guaranteed by using blind signature and mix-net, and robustness is provided through the threshold encryption scheme. By employing Java technology, we propose a way of typical implementation for internet voting system. Furthermore, PKI permits worldwide key distribution and achieve “one certificate/one vote” policy. Therefore, anyone can participate in the voting if he gets a certificate from Certificate Authority (CA). By the joint work between Korean and Japanese teams, the implementation aims to select MVPs in 2002 FIFA World Cup Korea-Japan$\^$TM/ in easy and friendly manner for any Internet user to participate and enjoy Internet voting.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.965-966
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• 2008

In this paper, a robust method is developed to precisely detect iris of both eyes. The method does not put any restrictions on the background. The method is based on AdaBoost for face and eye candidate points detection. Candidate points are post-processed and an iris pair is selected using mean crossing function and a convolution template.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.9-15
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• 2009

The fuzzy weighted mean classifier is one of the most common classification models and could achieve high performance by adjusting the weights. However, the weights were generally decided based on the experience of experts, which made the resulting classifiers to suffer the lack of consistency and objectivity. To resolve this problem, in this paper, a weight deciding method based on the statistics of the data is introduced, which ensures the learned classifiers to be consistent and objective. To investigate the effectiveness of the proposed methods, Iris data set available from UCI machine learning repository is used and promising results are obtained.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.148-153
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• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.71-76
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• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.241-242
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• 2007

In this paper, we propose a fuzzy vault system using iris data. The fuzzy vault, proposed by Juels and Sudan, has been used to protect cryptographic key with biometric information. In order to combine the fuzzy vault scheme with iris data, we used iris features extracted by ICA method and clustering technique. From our experimental results, we proved that the propose fuzzy vault system is robust to sensed environmental change.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.421-428
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• 2004

There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.19-29
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• 2006

As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.417-421
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• 2003

2000년 고기형 등이 발표한 땋임군상에서의 공개키 암호시스템은 후속적으로 다양한 이론적 분석 및 응용기법이 연구되고 있다 땋임군에서의 공개키 암호화기법과 서명기법은 기존에 제안되었으나 개인식별기법은 제안된 바가 없다. 본 논문에서 우리는 땋임군에서의 서명기법에 바탕을 둔 개인식별기법을 제안하고 그 안전성을 증명한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.175-182
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• 2010

The paper presents a novel algorithm for face and iris detection with the application for driver iris monitoring. The proposed algorithm consists of the following major steps: Skin-color segmentation, facial features segmentation, and iris positioning. For the skin-segmentation we applied a multi-layer perceptron to approximate the statistical probability of certain skin-colors, and filter out those with low probabilities. The next step segments the face region into the following categories: eye, mouth, eye brow, and remaining facial regions. For this purpose we propose a novel segmentation technique based on estimation of facial class probability density functions (PDF). Each facial class PDF is estimated on the basis of salient features extracted from a corresponding facial image region. Then pixels are classified according to the highest probability selected from four estimated PDFs. The final step applies the circular Hough transform to the detected eye regions to extract the position and radius of the iris. We tested our system on two data sets. The first one is obtained from the Web and contains faces under different illuminations. The second dataset was collected by us. It contains images obtained from video sequences recorded by a CCD camera while a driver was driving a car. The experimental results are presented, showing high detection rates.