• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.275-284
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• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• Journal of KIISE:Software and Applications
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• v.37 no.11
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• pp.859-865
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• 2010

In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.827-829
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• 2013

생체인식을 통한 개인 인증방법에는 지문인식과, 홍채인식 등이 활발하게 연구가 진행되고 있다. 본 논문에서는 생체인식을 통한 개인 인증 방법 중 우측 검지손가락 정맥을 이용한 방법을 사용하였다. 적외선 LED 8개를 이용하여 적외선을 손가락에 투과하여 CMOS카메라를 통하여 영상을 획득하는 정맥인식장치를 개발하고 영상을 채집한다. ROI영역을 추출하여 손가락 정맥인식을 위한 영상부분만 추출한다. 추출된 영상을 통하여 미디언 필터를 이용하여 noise를 제거하고 히스토그램 평활화를 통한 정맥영역을 부각시킨다. 특히 지역적 히스토그램 평활화를 통해서 보다 정확한 정맥의 영역을 찾는다. 지역적 히스토그램 평활화를 통한 영상을 이진화를 시키고 세선화를 통해서 이후 패터매칭을 통한 개인 인증방법에 대한 전처리 영상을 구한다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.41-45
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• 2007

기존의 생체인식 기술들은 노화에 따른 신체부위의 변형으로 인해 인식률 저하를 초래할 수 있으며 인식단계 시 눈과 같은 신체의 민감한 부분을 빛에 노출시키는 등의 불쾌감을 이용자에게 초래할 수 있다. 본 논문에서는 기존 생체인식 시스템이 갖는 이러한 문제들을 보완하기 위해 손가락 정맥영상을 이용한 생체인식 시스템을 제안한다. 손가락 정맥의 경우 인식 절차가 단순하면서도 개인마다 고유한 특징을 충분히 포함하고 있다. 또한 인체 내부에 존재하는 특징으로 인해 외상이나 노화로 인한 변형의 가능성이 적으며 촬영 시 이용자의 거부감이나 불쾌감을 최소화 할 수 있다.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1464-1466
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• 2015

개인 인증을 위한 바이오인식 방법으로 홍채, 지문, 정맥 인식 등이 널리 사용되고 있다. 하지만 별도의 센서가 필요한 방법들이므로 스마트폰에서 활용하기에 적절하지 않다. 본 논문에서는 엄지손가락 특징을 이용한 새로운 바이오 인식방법을 제안한다. 엄지손가락을 이용한 바이오 인식 방법은 손가락을 촬영하여 영상정보를 획득하는 단계, 영상의 크기와 방향, 밝기를 정규화 하는 단계, 영상 정보로부터 손가락 경계, 손톱 모양, 마디 주름 등의 특징을 검출하는 단계를 포함한다. 제안하는 방법은 카메라가 장착된 스마트기기에서 별도의 센서 추가 없이 개인 인증을 위한 방법으로 활용될 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.687-689
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• 2021

정맥을 이용한 생체 인식 방법은 신체의 노화에 영향을 받지 않고 높은 사용 편의성과 변조의 위험이 적어 인증 수단으로 폭넓게 활용되고 있다. 그러나 가짜 정맥 영상을 통한 스푸핑 공격 위험이 존재한다. 이러한 문제를 해결하기 위해 실제 정맥 영상과 가짜 정맥 영상을 구분하는 기술이 필요하다. 본 연구에서는 실제 정맥 데이터의 마디와 뼈의 밝기 차이를 이용해 진짜 정맥 영상과 가짜 정맥 영상을 구분하는 기술을 연구했다.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.671-676
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• 2016

Recently, according to the limelight of Fintech, simple payment using biometric at smartphone is widely used. In this paper, we propose a new contactless biometric method using thumb image without additional sensors unlike previous biometrics such as fingerprint, iris, and vein recognition. In our method, length, width, and skin texture information are used as features. For that, illumination normalization, skin region segmentation, size normalization and alignment procedures are sequentially performed from the captured thumb image. Then, correlation coefficient is calculated for similarity measurement. To analyze recognition accuracy, genuine and imposter matchings are performed. At result, we confirmed the FAR of 1.68% at the FRR of 1.55%. In here, because the distribution of imposter matching is almost normal distribution, our method has the advantage of low FAR. That is, because 0% FAR can be achieved at the FRR of 15%, the proposed method is enough to 1:1 matching for payment verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.948-953
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• 2015

Recently, the finger vein recognition based on NIR and CCD sensor camera is investigating the technology to identify a personal using by biometrics. The performance difference of finger vein recognition is generated according to methods that are to separate the vein and background from noises such as finger thickness, ambient light, skin temperature, etc. To improve these problems, in this study, we are proposing the methods for rotation, ROI extraction, and enhancement of vein image captured by NIR LED and CCD camera, and were evaluated performances of these methods. In results of the experiment, the accuracy of the proposed method for image rotation and ROI extraction was 99.8%. And the proposed filter bank method in vein enhancement has shown better performance than retinex algorithm. The proposed method for results of these experimentations will provide better recognition rate when applied to the preprocessing of finger vein recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.423-430
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• 2013

Recently, the personal identification technologies using vein pattern of back of the hand, palm, and finger have been developed actively because it has the advantage that the vein blood vessel in the body is impossible to damage, make a replication and forge. However, it is difficult to extract clearly the vein region from captured vein images through common image prcessing based region segmentation method, because of the light scattering and non-uniform internal tissue by skin layer and inside layer skeleton, etc. Especially, it takes a long time for processing time and makes a discontinuity of blood vessel just in a image because it has non-uniform illumination due to use a locally different adaptive threshold for the binarization of acquired finger-vein image. To solve this problem, we propose illumination normalization based fast method for extracting the finger-vein region. The proposed method has advantages compared to the previous methods as follows. Firstly, for remove a non-uniform illumination of the captured vein image, we obtain a illumination component of the captured vein image by using a low-pass filter. Secondly, by extracting the finger-vein path using one time binarization of a single threshold selection, we were able to reduce the processing time. Through experimental results, we confirmed that the accuracy of extracting the finger-vein region was increased and the processing time was shortened than prior methods.