• 제목/요약/키워드: reconstruction of the nonlinear information

검색결과 46건 처리시간 0.037초

Numerical Reconstruction and Pattern Recognition using Integral Imaging

  • Yeom, Seo-Kwon
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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    • pp.1131-1134
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    • 2008
  • In this invited paper, numerical reconstruction and pattern recognition using integral imaging are overviewed. The computational integral imaging method reconstructs three-dimensional information at arbitrary depth-levels. Photon-counting nonlinear matched filtering combined with the computational reconstruction provides promising results for the application of low-light level recognition.

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Three-Dimensional Automatic Target Recognition System Based on Optical Integral Imaging Reconstruction

  • Lee, Min-Chul;Inoue, Kotaro;Cho, Myungjin
    • Journal of information and communication convergence engineering
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    • 제14권1호
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    • pp.51-56
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    • 2016
  • In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

모폴로지 재구성과 비선형 확산을 적용한 영상 분할 방법 (An Image Segmentation method using Morphology Reconstruction and Non-Linear Diffusion)

  • 김창근;이귀상
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제32권6호
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    • pp.523-531
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    • 2005
  • 확산(Diffusion)을 이용한 기존의 칼라영상 분할은 확산의 횟수가 반복될수록 경계선 정보가 적절히 유지되지 못하거나 잡음을 제거하지 못함으로써 워터쉐드(Watershed) 알고리즘을 적용하는 경우, 과분할을 피할 수 없다는 단점을 갖고 있다. 본 논문에서는 수리 형태학(Mathematical Morphology)과 비선형 확산(Non-Linear Diffusion)을 함께 적용하여 과분할의 문제점을 제거한 워터쉐드 결과를 얻을 수 있는 칼라영상 분할방법을 제안한다. 임의의 칼라 영상을 LUV 색상공간으로 변환하여, 그 각각의 색상공간에 수리 형태학을 응용한 재구성에 의한 닫힘(Reconstruction) 연산과 비선형 확산을 함께 적용하여 경계선을 적절히 유지하면서 잡음을 제거한 단순 영상을 획득할 수 있다. 이 영상에서 칼라 영상의 기울기(Gradient) 정보를 획득하고, 워터쉐드 알고리즘을 적용하여 영상을 분할한다. 실험 결과, 기존의 방법보다 과분할이 현저히 제거되고, 칼라 영상이 매우 효과적으로 분할됨을 확인하였다

컴퓨터 집적 영상 복원 방법을 이용한 비선형 3D 영상 상관기 (Nonlinear 3D image correlator using computational integral imaging reconstruction method)

  • 신동학;홍석민;김경원;이병국
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2012년도 춘계학술대회
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    • pp.155-157
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    • 2012
  • 본 논문에서는 집적 영상 기술에 기반한 컴퓨터 3D 영상 복원을 이용하여 비선형 3D 영상 상관기를 제안한다. 제안하는 방법에서는 먼저 기준 3D 물체와 목표 3D 물체의 요소 영상들을 렌즈 어레이를 통해 픽업한다. 이 픽업된 영상에 컴퓨터 집적 영상 복원 방법을 사용하여 목표 평면 영상과 기준 평면 영상들이 복원된다. 복원된 기준 평면 영상과 목표 평면 영상들 간의 비선형 상호상관을 통해 인식을 수행한다. 제안된 방법의 유용함을 보이기 위해 기존의 방법과 비교하여 기초적인 상관관계 실험을 수행하고 그 결과를 발표한다.

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고속 컴퓨터 집적 영상 복원 방법을 이용한 비선형 3D 영상 상관기 (Nonlinear 3D Image Correlator Using Fast Computational Integral Imaging Reconstruction Method)

  • 신동학;이준재
    • 한국정보통신학회논문지
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    • 제16권10호
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    • pp.2280-2286
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    • 2012
  • 본 논문에서는 고속 컴퓨터 집적 영상 복원 방법을 이용하여 새로운 형태의 3D 비선형 상관기를 제안한다. 고속 컴퓨터 집적 영상 복원 방법을 구현하기 위해서 기존의 방법에서 확대 과정을 제거함으로서 고속 계산이 가능하다. 제안하는 상관기는 먼저 기준 물체와 목표 물체의 요소 영상들을 렌즈 배열을 통해 픽업한다. 이 픽업된 영상에 고속 컴퓨터 집적 영상 복원 방법을 사용하여 목표 평면 영상과 기준 평면 영상들이 복원된다. 복원된 기준 평면 영상과 목표 평면 영상들 간의 비선형 상호상관을 통해 인식을 수행한다. 비선형 상관 연산의 사용은 상관기의 3D 물체 인식 성능 향상시킬 수 있다. 제안된 방법의 유용함을 보이기 위해 기존의 방법과 비교하여 기초적인 상관관계 실험을 수행하고 그 결과를 보고한다.

Phase Error Reduction for Multi-frequency Fringe Projection Profilometry Using Adaptive Compensation

  • Cho, Choon Sik;Han, Junghee
    • Current Optics and Photonics
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    • 제2권4호
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    • pp.332-339
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    • 2018
  • A new multi-frequency fringe projection method is proposed to reduce the nonlinear phase error in 3-D shape measurements using an adaptive compensation method. The phase error of the traditional fringe projection technique originates from various sources such as lens distortion, the nonlinear imaging system and a nonsinusoidal fringe pattern that can be very difficult to model. Inherent possibility of phase error appearing hinders one from accurate 3-D reconstruction. In this work, an adaptive compensation algorithm is introduced to reduce adaptively the phase error resulting from the fringe projection profilometry. Three different frequencies are used for generating the gratings of projector and conveyed to the four-step phase-shifting procedure to measure the objects of very discontinuous surfaces. The 3-D shape results show that this proposed technique succeeds in reconstructing the 3-D shape of any type of objects.

3D Reconstruction using three vanishing points from a single image

  • Yoon, Yong-In;Im, Jang-Hwan;Kim, Dae-Hyun;Park, Jong-Soo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -2
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    • pp.1145-1148
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    • 2002
  • This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera and the problem of recovering 3D models from three vanishing points of box scene. Our approach is to compute only three vanishing points without this information such as the focal length, rotation matrix, and translation from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector ν. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by the standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

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불량애자 검출을 위한 비젼 기반 전파 신경망 (Propagation Neural Networks based on vision techniques for detecting of Faulty Insulator)

  • 김종만;김영민;황종선;박현철;임성호
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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    • pp.1097-1102
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    • 2002
  • For detecting of Faulty Insulator, a new Lateral Information Propagation Networks (LIPN) has been proposed. Energized insulator is reduced the rate of insulation extremely, and taken the results dirty and injured. It is necessary to be actions that detect the faulty insulator and exchange the new one. And thus, we have designed the LIPN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through several simulation experiments,real time reconstruction of the nonlinear image information is processed.

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산업 현장의 안전거리 계측을 위한 동적 계획 신경회로망 (A Dynamic Programming Neural Network to find the Safety Distance of Industrial Field)

  • 김종만;김원섭;김영민;황종선;박현철
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2001년도 기술교육위원회 창립총회 및 학술대회 의료기기전시회
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    • pp.23-27
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    • 2001
  • Making the safety situation from the various work system is very important in the industrial fields. The proposed neural network technique is the real titre computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objests during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of obejects. All of them request much memory space and titre. Therefore the most reliable neural-network algorithm is drived for real time recognition of obejects, which is composed of a dynamic programming algorithm based on sequence matching techniques. And the real time reconstruction of nonlinear image information is processed through several simulations. I-D LIPN hardware has been composed, and the real time reconstruction is verified through the various experiments.

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정보데이터의 복원기법 응용한 실시간 하드웨어 신경망 (Realtime Hardware Neural Networks using Interpolation Techniques of Information Data)

  • 김종만;김원섭
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2007년도 추계학술대회 논문집
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    • pp.506-507
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    • 2007
  • Lateral Information Propagation Neural Networks (LIPN) is proposed for on-line interpolation. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed.

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