• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.441-443
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• 2009

Piezo Film Sensor를 이용하여 팔뚝의 상완 동맥에서 맥박 측정을 위한 센서부 최적 구조에 관한 연구를 하였다. 탈부착이 쉬운 팔뚝형 밴드 형태에 Piezo Film Sensor를 삽입하여 생체 신호를 측정 하였다. 센서부의 최적 구조를 알기 위해서 센서패드 구조물의 형태에서 매질 및 두께를 변화시켜 가면서 생체 신호의 크기를 비교하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.322-324
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• 2003

생체인식 기술은 현재까지 많은 발전을 거듭하고 있으며 국내에서도 연구는 물론 표준화작업 및 데이터 베이스 구축이 활발히 진행되고 있다. 생체인식은 신체의 여러 부분을 이용하는 방법과 습관에서 비롯된 특징을 이용하는 방법이 있는데, 본 연구에서는 이 중에서 개인의 필기습관 정보를 이용하여 인식하였다. 본 연구에서는 필기습관에 주목하여 서명하는 사람의 습관이 잘 드러나는 펜의 기울임과 눌림, 펜의 방위각도 둥의 성분이 표현되어지는 동적인 생채정보를 감지하고 특성을 추출할 수 있는 타블렛과 펜을 사용하여 서명정보를 추출한다. 이렇게 생성된 서명정보의 특징을 추출하기 위하여 패턴인식분야에 널리 활용하고 있는 주성분요소분석(PCA, Principal Component Analysis), 독립성분요소분석(ICA, Independent Component Analysis)기법에 적용하였다. 생성된 두 특징벡터 사이의 거리를 Euclidean Distance를 이용하여 구하고 Nearest Neighbor를 비교하여 인식률을 알아보고 교차인식(Cross Validation) 기법 중 하나인 Leave-One-Out 방법을 이용한 분류성능 측정을 통하여 데이터의 신뢰수준을 알아보았다.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.151-156
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• 2015

In this paper, we have proposed personal multimodal biometric authentication system based on face detection, recognition and speaker verification for smart-phone environment. Proposed system detect the face with Modified Census Transform algorithm then find the eye position in the face by using gabor filter and k-means algorithm. Perform preprocessing on the detected face and eye position, then we recognize with Linear Discriminant Analysis algorithm. Afterward in speaker verification process, we extract the feature from the end point of the speech data and Mel Frequency Cepstral Coefficient. We verified the speaker through Dynamic Time Warping algorithm because the speech feature changes in real-time. The proposed multimodal biometric system is to fuse the face and speech feature (to optimize the internal operation by integer representation) for smart-phone based real-time face detection, recognition and speaker verification. As mentioned the multimodal biometric system could form the reliable system by estimating the reasonable performance.

• Journal of the Korean Society of Visualization
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• v.5 no.1
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• pp.9-11
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• 2007

We introduce an in vivo imaging flow cytometer, which provides fluorescence images simultaneously with quantitative information on the cell population of interest in a live animal. As fluorescent cells pass through the slit of light focused across a blood vessel, the excited fluorescence is confocally detected. This cell signal triggers a strobe beam and a high sensitivity CCD camera that captures a snap-shot image of the cell as it moves down-stream from the slit. We demonstrate that the majority of signal peaks detected in the in vivo flow cytometer arise from individual cells. The instrument's capability to image circulating T cells and measure their speed in the blood vessel in real time in vivo is demonstrated. The cell signal irradiance variation, clustering percentage, and potential applications in biology and medicine are discussed.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.105-112
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• 2010

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.117-124
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• 2011

This study was realized the home network system for home care by bio-physical sensor system, to convey for the remote physical signal. The composition condition has four functions of displacement point for a Vision, Somatosensory, Vestibular and CNS that the basic measurement used to a Heart Rate, Temperature, Weight. Physical signal are decided to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a physical neuroceptor of sensory organ for the measurement such as a Vision, Somatosensory, Vestibular, CNS, BMI. There are to check a health care condition through a combination of physical organ with a posturography of a exercise. The service of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for the remote control health management system.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.6
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• pp.9-16
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• 2013

Bio-impedance measurement system(BMS) is non-invasive and easy to implement a measurement method that allows determining the water content of a patient. The measurement conditions, the hardware specifications and the configurations of BMS devices must be well chosen in order to get correct and reproducible results. BMS was then conducted for the limbs and the thoracic using a lock-in amplifier and LabView control system with a frequency range of 1kHz-100kHz. From both the measurement data and the simulation results, we verified that the parameters in the proposed equivalent model and the trend of impedance variation according to the multi-frequency of applied current source are similar to those of human body. We believe that the real-time BMS developed in this study is highly reliable and applicable to the research on the clinical characteristics of the human being's impedance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2237-2242
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• 2014

As Single households increases for reason of communication development, extending human life, there are many problems occuring all over the world. In order to solve this problem with an invasion of privacy and manintain a healthy life, this paper suggest non-contact type bio-signal measurement system using IR-Radar, displacement sensor and Pan-Tilt system. The proposed system can increse the distance of measured respiration from 1m to over 8m, which is comprised of two IR-Radar for location tracking, one displacement sensor for non-contact type bio-signal measurement and one stepping motor drive system. The proposed system is verified through experiments and were confirmed the possibility.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.159-166
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• 2012

Many biometrics-based user authentication schemes using smart cards have been proposed to improve the security weaknesses in user authentication system. In 2010, Chang et al. proposed an improved biometrics-based user authentication scheme without concurrency system which can withstand forgery attack, off-line password guessing attack, replay attack, etc. In this paper, we analyze the security weaknesses of Chang et al.'s scheme and we have shown that Chang et al.'s scheme is still insecure against man-in-the-middle attack, off-line biometrics guessing attack, and does not provide mutual authentication between the user and the server. And we proposed the improved scheme to overcome these security weaknesses, even if the secret information stored in the smart card is revealed. As a result, the proposed scheme is secure for the user authentication attack, the server masquerading attack, the man-in-the-middle attack, and the off-line biometrics guessing attack, does provide the mutual authentication between the user and the remote server. And, in terms of computational complexities, the proposed scheme is more effective than Chang et al.'s scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.1-9
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• 2020

As pet dogs rapidly increase in number, abandoned and lost dogs are also increasing in number. In Korea, animal registration has been in force since 2014, but the registration rate is not high owing to safety and effectiveness issues. Biometrics is attracting attention as an alternative. In order to increase the recognition rate from biometrics, it is necessary to collect biometric images in the same form as much as possible-from the face. This paper proposes a method to determine whether a dog is facing front or not in a real-time video. The proposed method detects the dog's eyes and nose using deep learning, and extracts five types of directional face information through the relative size and position of the detected face. Then, a machine learning classifier determines whether the dog is facing front or not. We used 2,000 dog images for learning, verification, and testing. YOLOv3 and YOLOv4 were used to detect the eyes and nose, and Multi-layer Perceptron (MLP), Random Forest (RF), and the Support Vector Machine (SVM) were used as classifiers. When YOLOv4 and the RF classifier were used with all five types of the proposed face orientation information, the face recognition rate was best, at 95.25%, and we found that real-time processing is possible.