• 제목/요약/키워드: Single System Image

검색결과 715건 처리시간 0.03초

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

  • Wu, Tengfei;Leng, Lu
    • Journal of Multimedia Information System
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    • 제8권1호
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    • pp.23-30
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    • 2021
  • Palmprint has become a popular biometric modality; however, palmprint recognition has not been conducted in video media. Video palmprint recognition (VPR) has some advantages that are absent in image palmprint recognition. In VPR, the registration and recognition can be automatically implemented without users' manual manipulation. A good-quality image can be selected from the video frames or generated from the fusion of multiple video frames. VPR in contactless mode overcomes several problems caused by contact mode; however, contactless mode, especially mobile mode, encounters with several revere challenges. Double-line-single-point (DLSP) assisted placement technique can overcome the challenges as well as effectively reduce the localization error and computation complexity. This paper modifies DLSP technique to reduce the invalid area in the frames. In addition, the valid frames, in which users place their hands correctly, are selected according to finger gap judgement, and then some key frames, which have good quality, are selected from the valid frames as the gallery samples that are matched with the query samples for authentication decision. The VPR algorithm is conducted on the system designed and developed on mobile device.

거리별 얼굴영상 자동 생성 방법을 이용한 원거리 얼굴인식 시스템 (Long Distance Face Recognition System using the Automatic Face Image Creation by Distance)

  • 문해민;반성범
    • 전자공학회논문지
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    • 제51권11호
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    • pp.137-145
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    • 2014
  • 본 논문에서는 지능형 영상 감시시스템을 위한 LDA기반 원거리 얼굴인식 알고리즘을 제안한다. 기존 단일 거리 얼굴영상을 학습으로 사용한 얼굴인식 알고리즘은 원거리로 갈수록 얼굴인식률이 떨어지는 문제점이 있다. 실제 거리별 얼굴영상을 사용한 방법은 얼굴인식률은 향상되지만 사용자가 직접 움직이며 학습용 거리별 얼굴영상을 취득해야하는 문제점이 있다. 그러므로 본 논문에서는 단일 거리에서 취득한 얼굴영상을 이용해 거리별 얼굴영상을 자동으로 생성하여 학습으로 사용하는 방법을 제안한다. 제안하는 방법은 기존 얼굴인식 방법과 동일한 수준의 사용자 협조에서 거리별 사용자 등록영상을 생성할 수 있는 장점이 있다. 실험결과, 제안한 알고리즘은 기존 단일 거리 학습영상 기반 알고리즘에 비해 근거리에서 평균 16.3%, 원거리에서 평균 18.0% 향상된 얼굴인식 성능을 나타냈고, 실제 거리별 얼굴영상을 사용한 방법보다 근거리에서 평균 4.3%감소했지만, 원거리에서는 동일한 얼굴인식 성능을 나타냈다.

회전 평면경과 단일 카메라를 이용한 거리측정 시스템의 정밀도 분석 (Precision Analysis of the Depth Measurement System Using a Single Camera with a Rotating Mirror)

  • 김형석;나상익;한후석
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권11호
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    • pp.626-633
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    • 2003
  • Theoretical analysis of the depth measurement system with the use of a single camera and a rotating mirror has been done. A camera in front of a rotating mirror acquires a sequence of reflected images, from which depth information is extracted. For an object point at a longer distance, the corresponding pixel in the sequence of images moves at a higher speed. Depth measurement based on such pixel movement is investigated. Since the mirror rotates along an axis that is in parallel with the vertical axis of the image plane, the image of an object will only move horizontally. This eases the task of finding corresponding image points. In this paper, the principle of the depth measurement-based on the relation of the pixel movement speed and the depth of objects have been investigated. Also, necessary mathematics to implement the technique is derived and presented. The factors affecting the measurement precision have been studied. Analysis shows that the measurement error increases with the increase of depth. The rotational angle of the mirror between two image-takings also affects the measurement precision. Experimental results using the real camera-mirror setup are reported.

기계 시각과 인공 신경망을 이용한 파란의 판별 (Detection of Surface Cracks in Eggshell by Machine Vision and Artificial Neural Network)

  • 이수환;조한근;최완규
    • Journal of Biosystems Engineering
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    • 제25권5호
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    • pp.409-414
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    • 2000
  • A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.

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리눅스 클러스터 시스템에서 단일 디스크 입출력 공간을 지원하는 효율적 디스크 공유 기법 (An Efficient Disk Sharing Technique supporting Single Disk I/O Space in Linux Cluster Systems)

  • 김태호;이종우;이재원;김성동;채진석
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제9권6호
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    • pp.635-645
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    • 2003
  • 가격 대 성능비가 좋다는 장점으로 인해 많이 사용되고 있는 클러스터 병렬 컴퓨터 시스템에서는 여러 노드에 산재해 있는 자원들을 사용자들이 투명하게 사용할 수 있도록 지원하는 것이 필수적이다. 본 논문에서는 클러스터 시스템에서 단일 디스크 입출력 공간을 지원하는 효율적인 디스크 공유 기법을 제안한다. 응용 수준이 아닌 운영 체제 내의 블록 장치 드라이버 수준에서 디스크 공유를 지원함으로써 사용자들은 로컬 및 원격 디스크를 구분할 필요 없이 클러스터 시스템 내의 모든 디스크들을 마치 로컬 디스크 인 것처럼 투명하게 사용할 수 있다. 기반 운영체제로는 리눅스를 사용하였으며, 실험 결과 단일 디스크 입출력 공간을 성공적으로 지원함과 동시에 비교적 단순한 전역 캐쉬 일관성 정책을 사용했음에도 성능 면에서 NFS에 비해 읽기 성능은 유사, 쓰기 성능은 월등히 향상됨을 확인할 수 있었다. 본 논문이 기여하는 바는 블록 장치 드라이버 수준에서 단일 디스크 입출력 공간을 지원하는 기법을 제안함으로써 블록 장치 드라이버에 비해 비교적 구현이 쉬운 기타 입출력 장치 드라이버에 대해서도 유사한 방식으로 단일 입출력 공간을 지원할 수 있도록 도움을 줄 수 있다는 점이다.

발전용 밸브누설 평가를 위한 다중계측 연구 (Study on the Multi-measuring Method for Evaluation of Internal Leak of Power Plant Valve)

  • 이상국;박성근;박종혁;김광홍;김영범
    • 동력기계공학회지
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    • 제11권3호
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    • pp.35-40
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    • 2007
  • Leak would happen because of the damage of high temperature and high-pressure valve in nuclear power plant. condition based prevention maintenance is essential by using the suitable method based on local condition. Energy loss prevention can prevent from an accurate test, Local actually and ability. The methods of test for high energy fluid leak at present are analysis of ${\Delta}T$, AE(Acoustic Emission) analysis, and thermal image. The result for test of secondary system in nuclear power plant Unit reveals that the AE occurred clearly in leakage situation, but thermal image didn't occur. It is identified that leak is occurred when the orifice located front and back of valve operates. It shows that making a impatient judgment by using the single method if it is leakage is containing uncertainty. So we think that using the Multi-Measuring method is more sound judgment than single-measuring method.

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A STUDY ON INDUSTRIAL GAMMA RAY CT WITH A SINGLE SOURCE-DETECTOR PAIR

  • Kim Jong-Bum;Jung Sung-Hee;Kim Jin-Sup
    • Nuclear Engineering and Technology
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    • 제38권4호
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    • pp.383-390
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    • 2006
  • Having its roots in medical applications, industrial gamma ray CT has opened up new roads far investigating and modeling industrial processes. Using a line of research related to industrial gamma ray CT, the authors set up a system of single source and detector gamma transmission tomography for wood timber and a packed bed phantom. The hardware of the CT system consists of two servo motors, a data logger, a computer, a radiation source and a radiation detector. One motor simultaneously moves the source and the detector for a parallel beam scanning, whereas the other motor rotates the scan table at a preset projection angle. The image is reconstructed from the measured projections by the filtered back projection method. The phantom was designed to simulate a cross section of a packed bed with a void. The radiation source was 20mCi of Cs-137 and the detector was a 1 inch $\times$ 1 inch NaI (TI) scintillator shielded by a lead collimator. The experimental gamma ray CT image has sufficient resolution to reveal air holes and the density distribution inside the phantom. The system could possibly be applied to a packed bed column or a pipe flow in a petrochemical plant.

통합 프린지 해석 시스템 개발 : 심한 잡음을 포함하는 간섭 이미지 해석용 (Development of Integrated fringe Analysis System: For Severe Noise-ridden Interferometric Image Analysis)

  • 강민구;주원종;차동진;강보선
    • 대한기계학회논문집B
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    • 제27권11호
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    • pp.1534-1541
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    • 2003
  • A new window-based, user-friendly fringe analysis system is developed, especially for analyzing noisy interferograms. The system integrates three major techniques, that is fringe tracking, Phase shifting, and Fourier transform, into a single shell by employing a unified procedure. Since the system is made in a modular fashion and all processing modules can be shared for any technique, a user can select necessary modules and easily edit the applying order of them based on the user's analysis strategy, which should be changed depending on the noise level of the image. The system provides a high-level GUI and a variety of image handling tools and therefore users can easily access the system and produce the optimal results without giving up in the middle of a process even for severely noise-contaminated interferometric images.

Deep Learning-based Image Data Processing and Archival System for Object Detection of Endangered Species

  • Choe, Dea-Gyu;Kim, Dong-Keun
    • Journal of information and communication convergence engineering
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    • 제18권4호
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    • pp.267-277
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    • 2020
  • It is important to understand the exact habitat distribution of endangered species because of their decreasing numbers. In this study, we build a system with a deep learning module that collects the image data of endangered animals, processes the data, and saves the data automatically. The system provides a more efficient way than human effort for classifying images and addresses two problems faced in previous studies. First, specious answers were suggested in those studies because the probability distributions of answer candidates were calculated even if the actual answer did not exist within the group. Second, when there were more than two entities in an image, only a single entity was focused on. We applied an object detection algorithm (YOLO) to resolve these problems. Our system has an average precision of 86.79%, a mean recall rate of 93.23%, and a processing speed of 13 frames per second.

생성적 적대 신경망을 이용한 함정전투체계 획득 영상의 초고해상도 영상 복원 연구 (A Study on Super Resolution Image Reconstruction for Acquired Images from Naval Combat System using Generative Adversarial Networks)

  • 김동영
    • 디지털콘텐츠학회 논문지
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    • 제19권6호
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    • pp.1197-1205
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    • 2018
  • 본 논문에서는 함정전투체계의 EOTS나 IRST에서 획득한 영상을 초고해상도 영상으로 복원한다. 저해상도에서 초고해상도의 영상을 생성하는 생성 모델과 이를 판별하는 판별 모델로 구성된 생성적 적대 신경망을 이용하고, 다양한 학습 파라미터의 변화를 통한 최적의 값을 제안한다. 실험에 사용되는 학습 파라미터는 crop size와 sub-pixel layer depth, 학습 이미지 종류로 구성되며, 평가는 일반적인 영상 품질 평가 지표에 추가적으로 특징점 추출 알고리즘을 함께 사용하였다. 그 결과, Crop size가 클수록, Sub-pixel layer depth가 깊을수록, 고해상도의 학습이미지를 사용할수록 더 좋은 품질의 영상을 생성한다.