• 제목/요약/키워드: adaptive background

검색결과 343건 처리시간 0.023초

Detection and Recognition of Illegally Parked Vehicles Based on an Adaptive Gaussian Mixture Model and a Seed Fill Algorithm

  • Sarker, Md. Mostafa Kamal;Weihua, Cai;Song, Moon Kyou
    • Journal of information and communication convergence engineering
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    • 제13권3호
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    • pp.197-204
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    • 2015
  • In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

A Study on a effective Information Compressor Algorithm for the variable environment variation using the Kalman Filter

  • Choi, Jae-Yun
    • 한국컴퓨터정보학회논문지
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    • 제23권4호
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    • pp.65-70
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    • 2018
  • This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

복잡한 영상에서 적응적 에지검출을 이용한 텍스트 추출 알고리즘 연구 (Text Extraction Algorithm in Complex Images using Adaptive Edge detection)

  • 신성;김선동;백영현;문성룡
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2007년도 하계종합학술대회 논문집
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    • pp.251-252
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    • 2007
  • The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

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QRS 파의 증대를 위한 신경망 ALE 설계 (Design of neural network based ALE for QRS enhancement)

  • 원상철;박종철;최한고
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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    • pp.217-220
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    • 2000
  • This paper describes the application of a neural network based adaptive line enhancer (ALE) for enhancement of the weak QRS complex corrupted with background noise. Modified fully-connected recurrent neural network is used as a nonlinear adaptive filter in the ALE. The connecting weights between network nodes as well as the parameters of the node activation function are updated at each iteration using the gradient descent algorithm. The real ECG signal buried with moderate and severe background noise is applied to the ALE. Simulation results show that the neural network based ALE performs well the enhancement of the QRS complex from noisy ECG signals.

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인간의 청각모델에 기초한 잡음환경에 적응된 잡음억압 시스템 (Adaptive Noise Suppression system based on Human Auditory Model)

  • 최재승
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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    • pp.421-424
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    • 2008
  • 본 논문에서는 다양한 배경잡음에 의해 열화된 음성을 강조하기 위하여 청각모델에 기초로 한 잡음환경에 적응된 잡음억압 시스템을 제안한다. 제안한 시스템은 먼저 유성음과 무성음의 구간을 검출한 후, 각 입력 프레임에서 적응적인 청각기강의 처리를 한다. 마지막으로 진폭성분과 위상성분이 포함된 신경회로망을 사용하여 잡음신호를 제거한 후에 음성을 강조하는 처리를 한다. 본 시스템은 신호대잡음비의 평가방법을 통하여 다양한 잡음에 의해서 열화된 음성신호에 대해서 유효하다는 것을 실험으로 확인한다.

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적응적 세분화 방법을 이용한 무요소법의 응력 해석에 관한 연구 (A Study on the Adaptive Refinement Method for the Stress Analysis of the Meshfree Method)

  • 한상을;강노원;주정식
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2008년도 정기 학술대회
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    • pp.8-13
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    • 2008
  • In this study, an adaptive node generation procedure in the radial point interpolation method is proposed. Since we set the initial configuration of nodes by subdivision of background cell, abrupt changes of inter-nodal distance between higher and lower error regions are unavoidable. This unpreferable nodal spacing induces additional errors. To obtain the smoothy nodal configuration, it's regenerated by local Delaunay triangulation algorithm This technique was originally developed to generate a set of well-shaped triangles and tetrahedra. To demonstrate the performance of proposed scheme, the results of making optimal nodal configuration with adaptive refinement method are investigated for stress concentration problems.

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Visual Attention Detection By Adaptive Non-Local Filter

  • Anh, Dao Nam
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권1호
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    • pp.49-54
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    • 2016
  • Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

Adaptive 3-Frame Difference 기반 템플릿을 이용한 객체 추적 (Object Tracking Using Template Based on Adaptive 3-Frame Difference)

  • 김헌기;이진형;강지운;조성원;김재민;정선태;장용석
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.357-360
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    • 2007
  • 물체를 추적하는데 있어서 추적하고자 하는 물체를 검출하여 템플릿을 만드는 것과 두 물체가 겹쳐지거나 다른 배경에 가려진 물체를 구분하여 추적하는 것은 물체 추적에 있어서 중요한 문제이다. 물체를 검출하여 템플릿을 만드는 방법으로 frame difference를 이용하면 천천히 움직이는 물체를 잘 구분할 수 없는 문제점이 있다. 이를 해결하기 위하여 본 논문에서는 adaptive 3-frame difference를 이용하여 정확한 물체의 템플릿을 생성하는 알고리즘을 제안한다.

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적응 확장 유한요소기법과 형상최적설계로의 응용 (An adaptive X-FEM and its application to shape optimization)

  • 유용균;허재성;;곽병만
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.538-543
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    • 2007
  • A procedure is proposed to generate optimal grid with minimal user intervention while keeping a prescribed level of accuracy, using an adaptive X-FEM and applied to shape optimization. In spite of various advantages of X-FEM, however, there are several obstacles for practical applications. Because of using a uniform background mesh and additional degree of freedoms for enrichment, an X-FEM is usually computationally more expensive than traditional finite element method. Furthermore, there are often accuracy problems. For an automatic procedure of optimal mesh generation, an h-adaptive scheme and a posteriori error estimation obtained by a post-processing process are utilized. The procedure is shown by 2-D shape optimization examples.

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구조변화 통계량을 이용한 적응적 지수평활법 (Adaptive Exponential Smoothing Method Based on Structural Change Statistics)

  • 김정일;박대근;전덕빈;차경천
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2006년도 추계학술대회
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    • pp.165-168
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    • 2006
  • Exponential smoothing methods do not adapt well to unexpected changes in underlying process. Over the past few decades a number of adaptive smoothing models have been proposed which allow for the continuous adjustment of the smoothing constant value in order to provide a much earlier detection of unexpected changes. However, most of previous studies presented ad hoc procedure of adaptive forecasting without any theoretical background. In this paper, we propose a detection-adaptation procedure applied to simple and Holt's linear method. We derive level and slope change detection statistics based on Bayesian statistical theory and present distribution of the statistics by simulation method. The proposed procedure is compared with previous adaptive forecasting models using simulated data and economic time series data.

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