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Fast Detection of Finger-vein Region for Finger-vein Recognition (지정맥 인식을 위한 고속 지정맥 영역 추출 방법)

  • Kim, Sung-Min;Park, Kang-Roung;Park, Dong-Kwon;Won, Chee-Sun
    • 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.

Method for Classification of Age and Gender Using Gait Recognition (걸음걸이 인식을 통한 연령 및 성별 분류 방법)

  • Yoo, Hyun Woo;Kwon, Ki Youn
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.11
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    • pp.1035-1045
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    • 2017
  • Classification of age and gender has been carried out through different approaches such as facial-based and audio-based classifications. One of the limitations of facial-based methods is the reduced recognition rate over large distances, while another is the prerequisite of the faces to be located in front of the camera. Similarly, in audio-based methods, the recognition rate is reduced in a noisy environment. In contrast, gait-based methods are only required that a target person is in the camera. In previous works, the view point of a camera is only available as a side view and gait data sets consist of a standard gait, which is different from an ordinary gait in a real environment. We propose a feature extraction method using skeleton models from an RGB-D sensor by considering characteristics of age and gender using ordinary gait. Experimental results show that the proposed method could efficiently classify age and gender within a target group of individuals in real-life environments.

A Beamforming Method for a Perturbed Linear Towed Array (비선형 형상 견인 어레이를 위한 빔형성 기법)

  • 김승일;도경철;오원천;윤대희;이충용
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.5
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    • pp.478-484
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    • 2002
  • Linear towed arrays (LTA) have a nonlinear shape due to tow vessel motion, ocean swells and currents. By reasons of nominally linear shape, various towed array shape estimation techniques have been developed since the perturbed shape cause the error in target detection. In this paper,, we propose the beamforming method for the perturbed LTA with simple structure. The proposed method linearizes a nonlinear phase of steering vector with position information measured by two reference sensors. It can be proved using some properties of Markov transition matrix, and iteration number of linearization process is decided by variance of cross phase difference. As a result of computer simulation in the ocean environment, beampattern of the proposed method is almost same with the ideal case in my type of array shape. In the signal-to-noise ratio (SNR) performance simlation, the DOA estimation performance of the proposed beamforming method is evaluated, and the comparison with Bartlett beamformer of the LTA shows that the proposed method can estimate. the spatial characteristic of sources more accuracy.

Comparative Study of Optimization Algorithms for Designing Optimal Aperiodic Optical Phased Arrays for Minimal Side-lobe Levels (비주기적 광위상배열에서 Side-lobe Level이 최소화된 구조 설계를 위한 최적화 알고리즘의 비교 연구)

  • Lee, Bohae;Ryu, Han-Youl
    • Korean Journal of Optics and Photonics
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    • v.33 no.1
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    • pp.11-21
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    • 2022
  • We have investigated the optimal design of an aperiodic optical phased array (OPA) for use in light detection and ranging applications. Three optimization algorithms - particle-swarm optimization (PSO), a genetic algorithm (GA), and a pattern-search algorithm (PSA) - were employed to obtain the optimal arrangement of optical antennas comprising an OPA. The optimization was performed to obtain the minimal side-lobe level (SLL) of an aperiodic OPA at each steering angle, using the three optimization algorithms. It was found that PSO and GA exhibited similar results for the SLL of the optimized OPA, while the SLL obtained by PSA showed somewhat different features from those obtained by PSO and GA. For an OPA optimized at a steering angle <45°, the SLL value averaged over all steering angles increased as the angle of optimization decreased. However, when the angle of optimization was larger than 45°, low average SLL values of <13 dB were obtained for all three optimization algorithms. This implies that an OPA with high signal quality can be obtained when the arrangement of the optical antennas is optimized at a large steering angle.

Detection of Tracheal Sounds using PVDF Film and Algorithm Establishment for Sleep Apnea Determination (PVDF 필름을 이용한 기관음 검출 및 수면무호흡 판정 알고리즘 수립)

  • Jae-Joong Im;Xiong Li;Soo-Min Chae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.2
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    • pp.119-129
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    • 2023
  • Sleep apnea causes various secondary disease such as hypertension, stroke, myocardial infarction, depression and cognitive impairment. Early detection and continuous management of sleep apnea are urgently needed since it causes cardio-cerebrovascular diseases. In this study, wearable device for monitoring respiration during sleep using PVDF film was developed to detect vibration through trachea caused by breathing, which determines normal breathing and sleep apnea. Variables such as respiration rate and apnea were extracted based on the detected breathing sound data, and a noise reduction algorithm was established to minimize the effect even when there is a noise signal. In addition, it was confirmed that irregular breathing patterns can be analyzed by establishing a moving threshold algorithm. The results show that the accuracy of the respiratory rate from the developed device was 98.7% comparing with the polysomnogrphy result. Accuracy of detection for sleep apnea event was 92.6% and that of the sleep apnea duration was 94.0%. The results of this study will be of great help to the management of sleep disorders and confirmation of treatment by commercialization of wearable devices that can monitor sleep information easily and accurately at home during daily life and confirm the progress of treatment.

Simulation and Evaluation of the KOMPSAT/OSMI Radiance Imagery (다목적 실용위성 해색센서 (OSMI)의 복사영상에 대한 모의 및 평가)

  • 반덕로;김용승
    • Korean Journal of Remote Sensing
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    • v.15 no.2
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    • pp.131-146
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    • 1999
  • The satellite visible data have been successfully applied to study the ocean color. Another ocean color sensor, the Ocean Scanning Multi-spectral Imager (OSMI) on the Korea Multi-Purpose Satellite (KOMPSAT) will be launched in 1999. In order to understand the characteristics of future OSMI images, we have first discussed the simulation models and procedures in detail, and produced typical patterns of radiances at visible bands by using radiative transfer models. The various simulated images of full satellite passes and Korean local areas for different seasons, water types, and the satellite crossing equator time (CET) are presented to illustrate the distribution of each component of radiance (i.e., aerosol scattering, Rayleigh scattering, sun glitter, water-leaving radiance, and total radiance). A method to evaluate the image quality and availability is then developed by using the characteristics of image defined as the Complex Signal Noise Ratio (CSNR). Meanwhile, a series of CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of OSMI images before the KOMPSAT will be placed in orbit. Finally, the quality and availability of OSMI images are quantitatively analyzed by the simulated CSNR image. It is hoped that the results would be useful to all scientists who are in charge of OSMI mission and to those who plan to use the data from OSMI.

DESIGN AND DEVELOPMENT OF MULTI-PURPOSE CCD CAMERA SYSTEM WITH THERMOELECTRIC COOLING I. HARDWARE (열전냉각방식의 범용 CCD 카메라 시스템 개발 I. 하드웨어)

  • Kang, Y.W.;Byun, Y.I.;Rhee, J.H.;Oh, S.H.;Kim, D.K.
    • Journal of Astronomy and Space Sciences
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    • v.24 no.4
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    • pp.349-366
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    • 2007
  • We designed and developed a multi-purpose CCD camera system for three kinds of CCDs; KAF-0401E($768{\times}512$), KAF-1602E($1536{\times}1024$), KAF-3200E($2184{\times}1472$) made by KODAK Co.. The system supports fast USB port as well as parallel port for data I/O and control signal. The packing is based on two stage circuit boards for size reduction and contains built-in filter wheel. Basic hardware components include clock pattern circuit, A/D conversion circuit, CCD data flow control circuit, and CCD temperature control unit. The CCD temperature can be controlled with accuracy of approximately $0.4^{\circ}C$ in the max. range of temperature, ${\Delta}33^{\circ}C$. This CCD camera system has with readout noise $6\;e^-$, and system gain $5\;e^-/ADU$. A total of 10 CCD camera systems were produced and our tests show that all of them show passable performance.

A Study on the Air Pollution Monitoring Network Algorithm Using Deep Learning (심층신경망 모델을 이용한 대기오염망 자료확정 알고리즘 연구)

  • Lee, Seon-Woo;Yang, Ho-Jun;Lee, Mun-Hyung;Choi, Jung-Moo;Yun, Se-Hwan;Kwon, Jang-Woo;Park, Ji-Hoon;Jung, Dong-Hee;Shin, Hye-Jung
    • Journal of Convergence for Information Technology
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    • v.11 no.11
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    • pp.57-65
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    • 2021
  • We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.