• Review of KIISC
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• v.5 no.3
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• pp.5-14
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• 1995

본 고에서는 정교한 칼라 복사기와 디지탈 영상처리 기법의 발달과 함께 보안성에 대한 요구가 증대되고 있는 크레딧카드, 은행카드, 운전면허, Membership 카드 등에 적용될 수 있는 패턴인식기법에 대해 알아본다. 개인 ID의 확인을 위해 사용될 수 있는 패턴들은 지문, 얼굴모양, 홍채패턴, 서체, 손가락 구조, 음성패턴, 타이핑 리듬 등이다. 이들 특성들로부터 개인의 ID를 확인할 수 있는 방법들을 기존의 제안들을 중심으로 살펴본다.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1125-1137
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• 2011

Recently, there have been previous research about the iris recognition in mobile device to increase portability, whose accuracy is affected by the quality of iris image. Iris image is affected by illumination environment during the image acquisition. The existing system has high accuracy in indoor environment. However the accuracy is degraded in outdoor environment, because the gray levels of iris patterns in image are changed, and ghost and eyelash shading regions are produced by the sunlight of various wavelengths into iris region. To overcome these problems, we propose new mobile iris camera system which uses the near-infrared (NIR) light illuminator of 850 nm and band pass filter (BPF) of 850 nm. To measure the performance of the proposed system, we compared it to the existing one with the iris images captured in indoor and outdoor sunlight environments in terms of the equal error rates (EER) based on false acceptance rate (FAR) and false rejection rate (FRR). The experimental result showed that the proposed system had the lower EERs than those of previous system by 0.96% (with frontal light in indoors), 4.94% (with frontal light in outdoor), 9.24% (with side light in outdoor), and 7% (with back light in outdoor), respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.237-240
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• 2001

In this work, we will present an iris pattern recognition method as a biometrically based technology for personal identification and authentication. For this, we propose a new algorithm for extraction unique feature from images of the iris of the human eye and representing these feature using the discrete fourier transform. From the computational simplicity of the adopted transform, we can obtain more fast and efficient results than previous ones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.705-708
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• 2018

Among biometrics commercialized for security, iris recognition technology has the most excellent security for the probability of the match between individuals is the lowest. Current commercialized iris recognition technology has excellent recognition ability, but this technology has a fatal drawback. Without the user's active cooperation, it cannot recognize the iris correctly. To make up for this weakness, recent trend of iris recognition development mounts a non-volunteering, unconstrained method. According to this information, the objective of this research is developing a module that can identify people iris from a video acquired by high performance infrared camera in a range of 3m and in a involuntary way. For this, we import images from the video and find people's face and eye positions from the images using Haar classifier trained through Cascade training method. finally, we crop the iris by Hough circle transform and compare it with data from the database to identify people.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1147-1155
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• 2005

This paper deals with Iris recognition as one of biometric techniques which is applied to identify a person using his/her behavior or congenital characteristics. The Iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D Iris pattern having a property of size invariant and using the fuzzy LDA which is further through four types of 2D Gabor wavelet. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use four different matching values obtained from four different directional Gabor wavelet and select the maximum value, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 300 Iris Patterns extracted from 50 subjects and finally got more higher than $90\%$ recognition rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.716-721
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• 2003

This paper deals with the iris recognition as one of biometric techniques which are applied to identify a person using his/her behavior or congenital characteristics. The iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D iris pattern having a property of size invariant and divide it into 24 sectors which are further through three types of 2D Gabor filters. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use three different matching values obtained from three different directional Gabor filters and select the maximum value among them, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 50 iris patterns extracted from 10 subjects and finally get more higher than 90% recognition rate.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.167-168
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• 2019

Lately, variety of algorithms using encryption technology has been adopted as methods of unlocking smartphone. It is advancing toward the direction to solve through human biometrics technology which has already succeeded in commercialization. These include finger print recognition, face recognition, and iris recognition. In this study, we selected biometrics recognition technology and pattern recognition and password input methods which are already commercialized as evaluation items. The evaluation items are five algorithms including finger print recognition, face recognition iris recognition, pattern recognition and password input method. Based on these algorithms, analytic hierarchy process is used to analyze the preference of smartphone users. Also, the theoretical implications are presented based on the analysis results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.121-130
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• 2005

In this paper, we propose a feature extraction method for iris recognition using wavelet transforms. The wavelet transform is fast and has a good localization characteristic. In particular, the low frequency band can be used as an effective feature vector. In iris recognition, the noise caused by eyelid the eyebrow, glint, etc may be included in iris. The iris pattern is distorted by noises by itself, and a feature extraction algorithm based on filter such as Wavelets, Gabor transform spreads noises into whole iris region. Namely, such noises degrade the performance of iris recognition systems a major problem. This kind of noise has adverse effect on performance. In order to solve these problems, we propose to divide the iris image into a number of sub-region and apply the wavelet transform to each sub-region. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform and region division noticeably improves recognition performance. However, it is noted that the processing time of the wavelet transform is much faster than that of the existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.281-286
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• 2003

Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.