• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.12 no.2
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• pp.221-225
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• 2009

Pancreatic disease is the most frequent cause of isolated splenic vein thrombosis. Splenic vein thrombosis causes a localized form of portal hypertension known as sinistral or left-sided portal hypertension. Splenic vein thrombosis may be complicated by the formation of gastric varices, with the potential of massive upper gastrointestinal bleeding. Whereas splenectomy is considered to be the treatment of choice for symptomatic splenic vein thrombosis, the role of splenectomy in the patient with asymptomatic splenic vein thrombosis remains controversial. We report a rare case of acute pancreatitis complicated by isolated asymptomatic splenic vein thrombosis. Recognition of this disease entity is important because the risk of secondary variceal bleeding, while uncommon, can be life-threatening.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.187-192
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• 2009

In this paper, we proposed an algorithm for personal identification of dorsal surface pattern of hand vein pattern using graph theory. Using dense ranee data images of the hand vein pattern, we used matching algorithm within the frame work of graph theory for the determination of the desired correspondence. Through preprocessing, the captured images are more sharp, clear and thinning. After thinning, the images are normalized and make graph with node and edge set. This normalized graph can make adjacent matrix. Each adjacent matrix from individual vein pattern are different. From examining the performance of individual vein patterns, we can approach performances well kind biometric technique.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.60-69
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• 2015

Labor attendance management has traditionally been carried out by writing a table for checking an attendance of labor, which requires a lot of time and effort. As electronic devices with additions such as barcodes, Quick Response codes, and Radio Frequency Identification(RFID) have been developed, however, automated labor attendance management systems have appeared. Recently, various types of labor recognition devices converged with biometrics (fingerprint, vein, face recognition, etc.) have been released. However, although these devices can be used to check attendance automatically, there is insufficient guidance when it comes to selecting the appropriate labor attendance management system for construction sites. Therefore, this study proposed a decision framework to determine which labor attendance management system would be suitable for a construction site and to select the labor recognition device. This study investigated different labor recognition devices, focusing on how they worked, and tested the performance of devices and their usability for construction labor attendance management. The test results showed that RFID is most suitable when verifying the attendance of many laborers over a short period of time. The devices for hand vein and fingerprint recognition did not function when there was a foreign material such as cement or paint on the laborer's hand, except for a deformed finger. Reflecting these test results, this study suggested a framework for selecting a labor attendance system and recognition device; this is expected to contribute to the development of more efficient labor management systems.

• 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.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.560-563
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• 1999

In this paper, we present an optimal hardware implementation for preprocessing of a person identification algorithm utilizing vein pattern of dorsal surface of hand. For the vein pattern recognition, the computational burden of the algorithm lies mainly in the preprocessing of the input images, especially in lowpass filtering. we could reduce the identification time to one tenth by hardware design of the lowpass filter compared to sequential computations. In terms of the computation accuracy, the simulation results show that the CSD code provided an optimized coefficient value with about 91.62% accuracy in comparison with the floating point implementation of current coefficient value of the lowpass filter. The post-simulation of a VHDL model has been performed by using the ModelSim$^{TM}$. The implemented chip operates at 20MHz and has the operational speed of 55.107㎳.㎳.

• 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.

• Korean Journal of Artificial Intelligence
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• v.5 no.2
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• pp.15-25
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• 2017

Recently, technologies are being developed to recognize and authenticate users using bioinformatics to solve information security issues. Biometric information includes face, fingerprint, iris, voice, and vein. Among them, face recognition technology occupies a large part. Face recognition technology is applied in various fields. For example, it can be used for identity verification, such as a personal identification card, passport, credit card, security system, and personnel data. In addition, it can be used for security, including crime suspect search, unsafe zone monitoring, vehicle tracking crime.In this thesis, we conducted a study to recognize faces by detecting the areas of the face through a computer webcam. The purpose of this study was to contribute to the improvement in the accuracy of Recognition of Face Based on CNN Algorithms. For this purpose, We used data files provided by github to build a face recognition model. We also created data using CNN algorithms, which are widely used for image recognition. Various photos were learned by CNN algorithm. The study found that the accuracy of face recognition based on CNN algorithms was 77%. Based on the results of the study, We carried out recognition of the face according to the distance. Research findings may be useful if face recognition is required in a variety of situations. Research based on this study is also expected to improve the accuracy of face recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.941-944
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• 2009

In this paper, we present a improved algorithm for thinning vein pattern. The vein image scanned using near infra-red is sliced in the horizontality or verticality direction, and then average value is gained from each slice image. Using curvature value changed from average value, search candidate part and extract vein pattern through re-searched candidate part in overlapping area. For the extracted vein pattern connecting, we proposed a DAL method that verify distance, angle and luminosity on pattern before tracking pattern extracted. The proposed improved thinning method is helpful for accurate connecting of vein pattern more than method used distance material in candidate part.