• 제목/요약/키워드: Image Signal Recognition

검색결과 185건 처리시간 0.036초

고속 Chirplet 분리기법을 이용한 VHF 대역 레이더 표적신호 모델링 및 해석 (Modeling and Analysis of Radar Target Signatures in the VHF-Band Using Fast Chirplet Decomposition)

  • 박지훈;김시호;채대영
    • 한국군사과학기술학회지
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    • 제22권4호
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    • pp.475-483
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    • 2019
  • Although radar target signatures(RTS), such as range profiles have played an important role for target recognition in the X-band radar, they would be less effective when a target is designed to have low radar cross section(RCS). Recently, a number of research groups have conducted the studies on the RTS in the VHF-band where such targets can be better detected than in the X-band. However, there is a lack of work carried out on the mathematical description of the VHF-band RTS. In this paper, chirplet decomposition is employed for modeling of the VHF-band RTS and its performance is compared with that of existing scattering center model generally used for the X-band. In addition, the discriminative signal analysis is performed by chirplet parameterization of range profiles from in an ISAR image. Because the chirplet decomposition takes long computation time, its fast form is further proposed for enhanced practicality.

음성 신호와 얼굴 표정을 이용한 감정인식 몇 표현 기법 (An Emotion Recognition and Expression Method using Facial Image and Speech Signal)

  • 주종태;문병현;서상욱;장인훈;심귀보
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.333-336
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    • 2007
  • 본 논문에서는 감정인식 분야에서 가장 많이 사용되어지는 음성신호와 얼굴영상을 가지고 4개의(기쁨, 슬픔, 화남, 놀람) 감정으로 인식하고 각각 얻어진 감정인식 결과를 Multi modal 기법을 이용해서 이들의 감정을 융합한다. 이를 위해 얼굴영상을 이용한 감정인식에서는 주성분 분석(Principal Component Analysis)법을 이용해 특징벡터를 추출하고, 음성신호는 언어적 특성을 배재한 acoustic feature를 사용하였으며 이와 같이 추출된 특징들을 각각 신경망에 적용시켜 감정별로 패턴을 분류하였고, 인식된 결과는 감정표현 시스템에 작용하여 감정을 표현하였다.

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뉴럴네트워크를 이용한 카메라 보정기법 개발 (Development of Camera Calibration Technique Using Neural-Network)

  • 장영희
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1997년도 추계학술대회 논문집
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    • pp.225-229
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    • 1997
  • This paper describes the camera calibration based-neural network with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes and inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed camera calibration is illustrated by simulation and experiment.

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Combining Object Detection and Hand Gesture Recognition for Automatic Lighting System Control

  • Pham, Giao N.;Nguyen, Phong H.;Kwon, Ki-Ryong
    • Journal of Multimedia Information System
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    • 제6권4호
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    • pp.329-332
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    • 2019
  • Recently, smart lighting systems are the combination between sensors and lights. These systems turn on/off and adjust the brightness of lights based on the motion of object and the brightness of environment. These systems are often applied in places such as buildings, rooms, garages and parking lot. However, these lighting systems are controlled by lighting sensors, motion sensors based on illumination environment and motion detection. In this paper, we propose an automatic lighting control system using one single camera for buildings, rooms and garages. The proposed system is one integration the results of digital image processing as motion detection, hand gesture detection to control and dim the lighting system. The experimental results showed that the proposed system work very well and could consider to apply for automatic lighting spaces.

레이저 거리계의 이론적 최소 분해능에 관한 연구 (A study on the theoretical minimum resolution of the laser range finder)

  • 차영엽;권대갑
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.644-647
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    • 1996
  • In this study the theoretical minimum resolution analysis of an active vision system using laser range finder is performed for surrounding recognition and 3D data acquisition in unknown environment. The laser range finder consists of a slitted laser beam generator, a scanning mechanism, CCD camera, and a signal processing unit. A laser beam from laser source is slitted by a set of cylindrical lenses and the slitted laser beam is emitted up and down and rotates by the scanning mechanism. The image of laser beam reflected on the surface of an object is engraved on the CCD array. In the result, the resolution of range data in laser range finder is depend on distance between lens center of CCD camera and light emitter, view and beam angles, and parameters of CCD camera.

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Bayesian rule에 기초한 고속 Paper currency 인식 시스템 개발 (Development of high-speed paper currency recognition system based on Bayesian rule)

  • 조연호;이상훈;서일홍
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2474-2476
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    • 2004
  • 지폐 인식 자동화기기가 여러 분야에 보편화되면서 다양한 지폐를 고속으로 처리할 수 있는 고속지폐 인식 자동화 기기가 요구되고 있다. 하지만 대부분의 지폐 인식 자동화 기기가 고속화에 적합하지 않은 구조로 설계되어 있고 신권 추가가 용이하지 않다. 본 논문은 고속 Paper Currency 인식 시스템에 적합한 범용 하드웨어 시스템과 Bayes Rule 기반의 고속 인식 알고리즘을 제안한다. 제안된 범용 하드웨어 구조는 고속의 CIS(Contact Image Sensor)와 DSP(Digital Signal Processor) 그리고 Dual Memory System으로 구성되었다. Bayes Rule에 기초한 고속 인식 알고리즘은 기존의 Paper Currency 인식 시스템에 사용되었던 기계학습 방법에 비해 신권 추가가 쉽고 적은 연산으로 권종을 판별할 수 있어 고속 지폐 인식 자동화기기에 적합하다. 본 논문에서는 제안된 방법들을 실제 자동화기기로 구현하여 그 유용성을 검증한다.

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CNN을 이용한 능동 소나 표적/비표적 분류 (Active Sonar Target/Non-target Classification using Convolutional Neural Networks)

  • 김동욱;석종원;배건성
    • 한국멀티미디어학회논문지
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    • 제21권9호
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    • pp.1062-1067
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    • 2018
  • Conventional active sonar technology has relied heavily on the hearing of sonar operator, but recently, many techniques for automatic detection and classification have been studied. In this paper, we extract the image data from the spectrogram of the active sonar signal and classify the extracted data using CNN(convolutional neural networks), which has recently presented excellent performance improvement in the field of pattern recognition. First, we divided entire data set into eight classes depending on the ratio containing the target. Then, experiments were conducted to classify the eight classes data using proposed CNN structure, and the results were analyzed.

A Proposal of Programmable Logic Architecture for Reconfigurable Computing

  • Iida, Masahiro;Sueyoshi, Toshinori
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1547-1550
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    • 2002
  • Reconfigurable computing is a new computing paradigm which has more potential in terms of performance and flexibility. Reconfigurable computing systems are opening a new era in digital signal processing such as multimedia, communication and consumer electronics because they can filter data rapidly and excel at pattern recognition, image process- ing and encryption. Although many reconfigurable computing systems use a conventional programmable device, they carry several serious problems to be solved. This paper proposes a logic block architecture of programmable device suit-able for the reconfigurable computing. Compared to conventional logic blocks, our logic block can improve implementation density, efficiency and speed.

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On a Novel Way of Processing Data that Uses Fuzzy Sets for Later Use in Rule-Based Regression and Pattern Classification

  • Mendel, Jerry M.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권1호
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    • pp.1-7
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    • 2014
  • This paper presents a novel method for simultaneously and automatically choosing the nonlinear structures of regressors or discriminant functions, as well as the number of terms to include in a rule-based regression model or pattern classifier. Variables are first partitioned into subsets each of which has a linguistic term (called a causal condition) associated with it; fuzzy sets are used to model the terms. Candidate interconnections (causal combinations) of either a term or its complement are formed, where the connecting word is AND which is modeled using the minimum operation. The data establishes which of the candidate causal combinations survive. A novel theoretical result leads to an exponential speedup in establishing this.

고주파 성분을 고려한 AWGN 제거 알고리즘 (AWGN Removal Algorithm Considering High Frequency Components)

  • 천봉원;김남호
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 춘계학술대회
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    • pp.481-483
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    • 2018
  • 최근 전자통신장비의 수요가 증가함에 따라 영상 및 신호처리의 중요성이 높아지고 있다. 하지만 디지털 신호에 발생하는 잡음은 송수신 과정에서 다양한 원인으로 발생하며 장비의 신뢰성 저하 및 오작동을 유발하고 있다. 특히 AWGN은 전자장비 대부분에서 발견할 수 있기 때문에 영상 인식, 추출, 분할 등 여러 분야에서 전처리 과정으로서 AWGN 제거가 필수적으로 이루어진다. 본 논문은 고주파 성분을 고려한 AWGN 제거 알고리즘을 제안하였다. 기존 방법들은 고주파 성분이 많은 영상에서 비교적 미흡한 성능을 보였으며, 이를 보완하기 위해 국부 마스크에 차영상을 가감한 필터 알고리즘을 제시하였다. 그리고 제안한 알고리즘의 성능을 입증하기 위해 PSNR 및 확대 영상을 이용하여 기존 방법과 비교하였다.

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