• Title/Summary/Keyword: Detection Techniques

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On the Improvement of Error Performance in the Differential Detector for 3-h CPM (3-h CPM 차동 검파기의 오율 성능 개선)

  • 홍의식;한영열
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.3
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    • pp.240-246
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    • 1992
  • In the paper, the differential detection techniques of 3-h CPM signals whose modulation index is varied periodically are proposed and their error performances are analyzed. We select the modulation index sets which are proper to the differential detection and propose the differential detectors which detect symbol with 3 bits per smapling period of 3T and detect a bit per sampling period of T. Applying the nonredundant error correction circuit and viterbi algorithm to differential detection of 3-h CPM. We ascertain the error performances are improved.

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Experiment on the Time-Reversal of Lamb Waves for the Application to Structural Damage Detection (구조물 손상진단을 위한 Lamb 파의 시간-역전현상에 대한 실험)

  • Go, Han-Suk;Lee, Chang-Ho;Lee, U-Sik
    • Proceedings of the KSR Conference
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    • 2007.11a
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    • pp.913-916
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    • 2007
  • In this paper, the possibility of time reversal phenomenon was investigated in damage detection of structure. In conventional lamb wave techniques, damage is identified by comparing the measured data (baseline signals) and the current data. But this method can lead to high false signal in the intact condition of structures due to environmental conditions of the structures. So in this studying, we investigate the possibility of damage detection in the aluminum plate using the time reversal phenomenon of lamb waves.

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Coordinates Matching in the Image Detection System For the Road Traffic Data Analysis

  • Kim, Jinman;Kim, Hiesik
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.35.4-35
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    • 2001
  • Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

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Face Detection Based on Thick Feature Edges and Neural Networks

  • Lee, Young-Sook;Kim, Young-Bong
    • Journal of Korea Multimedia Society
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    • v.7 no.12
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    • pp.1692-1699
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    • 2004
  • Many researchers have developed various techniques for detection of human faces in ordinary still images. Face detection is the first imperative step of human face recognition systems. The two main problems of human face detection are how to cutoff the running time and how to reduce the number of false positives. In this paper, we present frontal and near-frontal face detection algorithm in still gray images using a thick edge image and neural network. We have devised a new filter that gets the thick edge image. Our overall scheme for face detection consists of two main phases. In the first phase we describe how to create the thick edge image using the filter and search for face candidates using a whole face detector. It is very helpful in removing plenty of windows with non-faces. The second phase verifies for detecting human faces using component-based eye detectors and the whole face detector. The experimental results show that our algorithm can reduce the running time and the number of false positives.

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Design and Implementation of User-oriented Face Detection System for Application Developers (응용개발자를 위한 사용자 중심 얼굴검출 시스템 설계 및 구현)

  • Jang, Dae Sik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.4
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    • pp.161-170
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    • 2010
  • This paper provides a novel approach for a user oriented system for face detection system for application developers. Even though there are many open source or commercial libraries to solve the problem of face detection, they are still hard to use because they require specific knowledge on detail algorithmic techniques. The purpose of this paper is to come up with a high-level system for face detection with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions so that application developers can use them to express various problems. Once the conditions are expressed by developers, the interpreter proposed take the role to interpret the conditions, find and organize the optimal algorithms to solve the represented problem with corresponding conditions. A proof-of-concept is implemented and some example problems are tested and analyzed to show the ease of use and usability.

Human Hand Detection Using Color Vision (컬러 시각을 이용한 사람 손의 검출)

  • Kim, Jun-Yup;Do, Yong-Tae
    • Journal of Sensor Science and Technology
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    • v.21 no.1
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    • pp.28-33
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    • 2012
  • The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.

Hybrid Fuzzy Adaptive Wiener Filtering with Optimization for Intrusion Detection

  • Sujendran, Revathi;Arunachalam, Malathi
    • ETRI Journal
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    • v.37 no.3
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    • pp.502-511
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    • 2015
  • Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

A fault detection and recovery mechanism for the fault-tolerance of a Mini-MAP system (Mini-MAP 시스템의 결함 허용성을 위한 결함 감지 및 복구 기법)

  • Mun, Hong-Ju;Kwon, Wook-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.2
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    • pp.264-272
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    • 1998
  • This paper proposes a fault detection and recovery mechanism for a fault-tolerant Mini-MAP system, and provides detailed techniques for its implementation. This paper considers the fault-tolerant Mini-MAP system which has dual layer structure from the LLC sublayer down to the physical layer to cope with the faults of those layers. For a good fault detection, a redundant and hierarchical fault supervision architecture is proposed and its implementation technique for a stable detection operation is provided. Information for the fault location is provided from data reported with a fault detection and obtained by an additional network diagnosis. The faults are recovered by the stand-by sparing method applied for a dual network composed of two equivalent networks. A network switch mechanism is proposed to achieve a reliable and stable network function. A fault-tolerant Mini-MAP system is implemented by applying the proposed fault detection and recovery mechanism.

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Performance Comparison of Coherent and Non-Coherent Detection Schemes in LR-UWB System

  • Kwon, Soonkoo;Ji, Sinae;Kim, Jaeseok
    • Journal of Communications and Networks
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    • v.14 no.5
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    • pp.518-523
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    • 2012
  • This paper presents new coherent and non-coherent detection methods for the IEEE 802.15.4a low-rate ultra-wideband physical layer with forward error correction (FEC) coding techniques. The coherent detection method involving channel estimation is based on the correlation characteristics of the preamble signal. A coherent receiver uses novel iterated selective-rake (IT-SRAKE) to detect 2-bit data in a non-line-of-sight channel. The non-coherent detection method that does not involve channel estimation employs a 2-bit data detection scheme using modified transmitted reference pulse cluster (M-TRPC) methods. To compare the two schemes, we have designed an IT-SRAKE receiver and a MTRPC receiver using an IEEE 802.15.4a physical layer. Simulation results show the performance of IT-SRAKE is better than that of the M-TRPC by 3-9 dB.

Intelligent Electronic Nose System for Detection of VOCs in Exhaled Breath

  • Byun, Hyung-Gi;Yu, Joon-Bu
    • Journal of Sensor Science and Technology
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    • v.28 no.1
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    • pp.7-12
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    • 2019
  • Significant progress has been made recently in detection of highly sensitive volatile organic compounds (VOCs) using chemical sensors. Combined with the progress in design of micro sensors array and electronic nose systems, these advances enable new applications for detection of extremely low concentrations of breath-related VOCs. State of the art detection technology in turn enables commercial sensor systems for health care applications, with high detection sensitivity and small size, weight and power consumption characteristics. We have been developing an intelligent electronic nose system for detection of VOCs for healthcare breath analysis applications. This paper reviews our contribution to monitoring of respiratory diseases and to diabetic monitoring using an intelligent electronic nose system for detection of low concentration VOCs using breath analysis techniques.