• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.672-673
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• 2016

최근 위변조에 의한 본인 인증 관련 사고가 급증하였으며 지문인식 밑 기타 다양한 인증시스템이 연구되고 있다. 최근에는 사람의 지정맥을 활용한 인증 시스템의 개발에 차세대 인증 시스템으로 연구가 활발히 진행되고 있다. 지정맥 인증 기술은 손가락 두 번째 마디 내 정맥을 말한다. 지정맥의 특성은 겉으로 보이지 않고 사람마다 패턴이 다르기 때문에 위 변조가 불가능하다. 뿐만아니라 지정맥 인증은 인증 절차가 간단하고, 보안성이 매우 높은 것으로 알려져 있다. 본 연구는 기존 지문을 이용한 출/퇴근 정보는 각종 관련 사고를 유발 시킬 수 있음을 방지하고자 지정맥을 이용한 본인 인증에 대한 보안성을 높이고, 각종 부당 취득 사고(추가근무)를 미연에 방지할 수 있으며, 지정맥을 이용해 출입/퇴근 시간을 기록하며 기록된 데이터로 지각/추가 근무 시간을 정확하게 측정 할 수 있다. 본 논문의 연구 결과물을 통해서 지정맥을 이용한 출/퇴근 정보를 데이터베이스/엑셀/텍스트에 저장하고, 기록된 정보를 이용해 지각/추가근무 시간을 정확하게 산출하여 각종사고를 미연에 방지할 수 있음을 확인하였다.

• 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 Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.23-31
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• 2009

Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.159-168
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• 2021

As the information age enters, the use of biometrics using the body is gradually increasing because it is very important to accurately recognize and authenticate each individual's identity for information protection. Among them, finger vein authentication technology is receiving a lot of attention because it is difficult to forge and demodulate, so it has high security, high precision, and easy user acceptance. However, the accuracy may be degraded depending on the algorithm for identification or the surrounding light environment. In this paper, we designed and manufactured a side-type finger vein recognizer that is highly versatile among finger vein measuring devices, and authenticated using the deep learning model of DenseNet-201 for high accuracy and recognition rate. The performance of finger vein authentication technology according to the influence of the infrared light source used and the surrounding visible light was analyzed through simulation. The simulations used data from MMCBNU_6000 of Jeonbuk National University and finger vein images taken directly were used, and the performance were compared and analyzed using the EER.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.197-202
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• 2021

Biometric technology using finger veins is receiving a lot of attention due to its high security, convenience and accuracy. And the recent development of deep learning technology has improved the processing speed and accuracy for authentication. However, the training data is a subset of real data not in a certain order or method and the results are not constant. so the amount of data and the complexity of the artificial neural network must be considered. In this paper, the deep learning model of Inception-Resnet-v2 was used to improve the high accuracy of the finger vein recognizer and the performance of the authentication system, We compared and analyzed the performance of the deep learning model of DenseNet-201. The simulations used data from MMCBNU_6000 of Jeonbuk National University and finger vein images taken directly. There is no preprocessing for the image in the finger vein authentication system, and the results are checked through EER.

• 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 Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.365-367
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• 2016

Recently, the importance of personal information security has emerged. In particular, the importance of biometrics such as voice recognition, fingerprint recognition, face recognition has been highlighted in various fields such as access control, banking security, personal PC security and so on. But if such conventional security techniques are likely to be recognized by an external factor failure. In contrast, if the vein recognition is impossible to copy and counterfeit. Therefore less likely to fail due to external factors has the advantage. In this paper, propose a preprocessing method to improve on the existing vein pattern recognition with high reliability than existing biometric technologies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• Journal of Chest Surgery
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• v.5 no.1
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• pp.13-18
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• 1972

In 1835,Schlesinger first described a case of subisthmlc lower thoracic aortic coarctation. Since Olim`s unsuccessful reconstructive surgery in 1949 and Beattie`s first successful resection with homograft replacement on such a lesion in 1951 were reported,about 20 cases of atypical aortic coarctation had been treated by definitive surgery until 1964. In Korea, only 2 cases of atypical aortic coarctation treated by bypass graft were reported until now. This is the third case-report treated by reconstructive surgery. The patient,11 year old girl who had 2 year history of headache, visual weakness, intermittent claudlcation, and general weakness, was first diagnosed of having the hypertension due to atypical coarctation by the findings of high blood pressure[170/110mmHg] at the upper extremity and weak pulsation on both femoral artery,murmur on the epigastrium, absence of aortic knob, and aorto graphy. Aortography demonstrated the isolated segmental narrowing[length 5cm, diameter 0.4cm] at the level of aortic hiatus 2cm above celiac arterial origin, the dilated right 9th, 10th, 11th intercostal arteries with multiple dimunitive collaterals and no associated abnormalities in the other arteries. Preoperatlve positive findings were strong positive mantoux test, high AST[720 units]. transient mild cardiomegaly with right lung infiltration on chest X-ray and suggestive left ventricular hypertrophy on ECG. On December 1970, through separate left thoracotomy and abdominal approach, bypass graft between descending thoracic aorta and abdominal aorta below renal artery was performed. The operation was first successful with satisfactory reduction of hypertension on the upper trunk[postoperatlve 130/80mmHg] and strong pulsation on the lower extremities[postop. O, postop. 140/100mmHg]. However,6 weeks after surgery, she expired of sudden hemoptysis and shock due to anastomotic leak within the thorax. Operative finding disclosed that the affected aorta was firm, with rich periaortic fibrosis and the outer diameter of stenotic site was not attenuated. Histopathology of the resected specimen was also compatible with primary arteritis.