• Title/Summary/Keyword: Detection,

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Kidney's feature point extraction based on edge detection using SIFT algorithm in ultrasound image (Edge detection 기반의 SIFT 알고리즘을 이용한 kidney 특징점 검출 방법)

  • Kim, Sung-Jung;Yoo, JaeChern
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.89-90
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    • 2019
  • 본 논문에서는 ultrasound image Right Parasagittal Liver에 edge detection을 적용한 후, 특징점 검출 알고리즘인 Scale Invarient Feature Transfom(SIFT)를 이용하여 특징점의 위치를 살펴보도록 한다. edge detection 알고리즘으로는 Canny edge detection과 Prewitt edge detection을 적용하기로 한다.

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Development of a dual-mode energy-resolved neutron imaging detector: High spatial resolution and large field of view

  • Wenqin Yang;Jianrong Zhou;Jianqing Yang;Xingfen Jiang;Jinhao Tan;Lin Zhu;Xiaojuan Zhou;Yuanguang Xia;Li Yu;Xiuku Wang;Haiyun Teng;Jiajie Li;Yongxiang Qiu;Peixun Shen;Songlin Wang;Yadong Wei;Yushou Song;Jian Zhuang;Yubin Zhao;Junrong Zhang;Zhijia Sun;Yuanbo Chen
    • Nuclear Engineering and Technology
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    • v.56 no.7
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    • pp.2799-2805
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    • 2024
  • Energy-resolved neutron imaging is an effective way to investigate the internal structure and residual stress of materials. Different sample sizes have varying requirements for the detector's imaging field of view (FOV) and spatial resolution. Therefore, a dual-mode energy-resolved neutron imaging detector was developed, which mainly consisted of a neutron scintillator screen, a mirror, imaging lenses, and a time-stamping optical fast camera. This detector could operate in a large FOV mode or a high spatial resolution mode. To evaluate the performance of the detector, the neutron wavelength spectra and the multiple spatial resolution tests were conducted at CSNS. The results demonstrated that the detector accurately measured the neutron wavelength spectra selected by a bandwidth chopper. The best spatial resolution was about 20 ㎛ in high spatial resolution mode after event reconstruction, and a FOV of 45.0 mm × 45.0 mm was obtained in large FOV mode. The feasibility was validated to change the spatial resolution and FOV by replacing the scintillator screen and adjusting the lens magnification.

Fire Detection Algorithm Based On Motion Information and Color Information Analysis (움직임 정보와 칼라정보 분석을 통한 화재검출 알고리즘)

  • Choi, Hong-seok;Moon, Kwang-seok;Kim, Jong-nam;Park, Seung-seob
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.180-188
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    • 2016
  • In this paper, we propose a fire detection algorithm based on motion information and color information analysis. Conventional fire detection algorithms have as main problem the difficulty to detect fire due to external light, intensity, background image complexity, and little fire diffusion. So we propose a fire detection algorithm that accurate and fast. First, it analyzes the motion information in video data and then set the first candidate. Second, it determines this domain after analyzing the color and the domain. This algorithm assures a fast fire detection and a high accuracy compared with conventional fire detection algorithms. Our algorithm will be useful to real-time fire detection in real world.

CNN based IEEE 802.11 WLAN frame format detection (CNN 기반의 IEEE 802.11 WLAN 프레임 포맷 검출)

  • Kim, Minjae;Ahn, Heungseop;Choi, Seungwon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.16 no.2
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    • pp.27-33
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    • 2020
  • Backward compatibility is one of the key issues for radio equipment supporting IEEE 802.11, the typical wireless local area networks (WLANs) communication protocol. For a successful packet decoding with the backward compatibility, the frame format detection is a core precondition. This paper presents a novel frame format detection method based on a deep learning procedure for WLANs affiliated with IEEE 802.11. Considering that the detection performance of conventional methods is degraded mainly due to the poor performances in the symbol synchronization and/or channel estimation in low signal-to-noise-ratio environments, we propose a novel detection method based on convolutional neural network (CNN) that replaces the entire conventional detection procedures. The proposed deep learning network provides a robust detection directly from the receive data. Through extensive computer simulations performed in the multipath fading channel environments (modeled by Project IEEE 802.11 Task Group ac), the proposed method exhibits superb improvement in the frame format detection compared to the conventional method.

The study on configuration method for the vehicle-based train position detection (차상기반 열차위치검지방식의 구성방안 연구)

  • Shin, Kyung-Ho;Jung, Eui-Jin;Kim, Jong-Ki
    • Proceedings of the KIEE Conference
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    • 2006.10d
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    • pp.238-240
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    • 2006
  • For the method of train position detection, ground-based train position estimation mainly has been applied so far. Ground-based position detection is the way to detect train current positions by installing train position equipments on railroad lines. However, the ground-based methods should install detection equipments on each section, and can only be able to detect train positions from main command center. So this method has several disadvantages such as an discontinuous position detection, an increment in cost of installation and maintenance. To make possible continuous train position detection, and to minimize amount of the cost, the vehicle-based position detection method should be chosen to determine train positions by loading position equipments on vehicles. In this paper, to realize the vehicle-based train position detection method, configuration scheme of train position detection equipment is suggested by using GPS, inertial sensor, speed sensor and its performance is verified by simulations.

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Detection Range Estimation Algorithm for Active SONAR System and Application to the Determination of Optimal Search Depth (능동 소나 체계에서의 표적 탐지거리 예측 알고리즘과 최적 탐지깊이 결정에의 응용)

  • 박재은;김재수
    • Journal of Ocean Engineering and Technology
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    • v.8 no.1
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    • pp.62-70
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    • 1994
  • In order to estimate the detection range of a active SONAR system, the SONAR equation is commonly used. In this paper, an algorithm to calculate detection range in active SONAR system as function of SONAR depth and target depth is presented. For given SONAR parameters and environment, the transmission loss and background level are found, signal excess is computed. Using log-normal distribution, signal excess is converted to detection probability at each range. Then, the detection range is obtained by integrating the detection probability as function of range for each depth. The proposed algorithm have been applied to the case of omni-directional source with center frequency 30Hz for summer and winter sound profiles. It is found that the optimal search depth is the source depth since the detection range increase at source depth where the signal excess is maximized.

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Measure of Effectiveness Analysis of Passive SONAR System for Detection (수동소나시스템에서 탐지효과도 분석)

  • Cho, Jung-Hong;Kim, Jea-Soo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.3
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    • pp.272-287
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    • 2012
  • The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

Face Detection by Eye Detection with Progressive Thresholding

  • Jung, Ji-Moon;Kim, Tae-Chul;Wie, Eun-Young;Nam, Ki-Gon
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1689-1694
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    • 2005
  • Face detection plays an important role in face recognition, video surveillance, and human computer interface. In this paper, we present a face detection system using eye detection with progressive thresholding from a digital camera. The face candidate is detected by using skin color segmentation in the YCbCr color space. The face candidates are verified by detecting the eyes that is located by iterative thresholding and correlation coefficients. Preprocessing includes histogram equalization, log transformation, and gray-scale morphology for the emphasized eyes image. The distance of the eye candidate points generated by the progressive increasing threshold value is employed to extract the facial region. The process of the face detection is repeated by using the increasing threshold value. Experimental results show that more enhanced face detection in real time.

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Microcystin Detection Characteristics of Fluorescence Immunochromatography and High Performance Liquid Chromatography

  • Pyo, Dong-Jin;Park, Geun-Young;Choi, Jong-Chon;Oh, Chang-Suk
    • Bulletin of the Korean Chemical Society
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    • v.26 no.2
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    • pp.268-272
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    • 2005
  • Different detection characteristics of fluorescence immunochromatography method and high performance liquid chromatography (HPLC) method for the analysis of cyanobacterial toxins were studied. In particular, low and high limits of detection, detection time and reproducibility and detectable microcystin species were compared when fluorescence immunochromatography method and high performance liquid chromatography method were applied for the detection of microcystin (MC), a cyclic peptide toxin of the freshwater cyanobacterium Microcystis aeruginosa. A Fluorescence immunochromatography assay system has the unique advantages of short detection time and low detection limit, and high performance liquid chromatography detection method has the strong advantage of individual quantifications of several species of microcystins.

Implementation of Distributed Intrusion Detection System based on Protocols (프로토콜 기반 분산 침입탐지시스템 설계 및 구현)

  • Yang, Hwan Seok
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.1
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    • pp.81-87
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    • 2012
  • Intrusion Detection System that protects system safely is necessary as network technology is developed rapidly and application division is wide. Intrusion Detection System among others can construct system without participation of other severs. But it has weakness that big load in system happens and it has low efficient because every traffics are inspected in case that mass traffic happen. In this study, Distributed Intrusion Detection System based on protocol is proposed to reduce traffic of intrusion detection system and provide stabilized intrusion detection technique even though mass traffic happen. It also copes to attack actively by providing automatic update of using rules to detect intrusion in sub Intrusion Detection System.