• 제목/요약/키워드: 3D image reconstruction

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Balloon을 이용한 3차원 Visible human 컬러 영상의 분할 방법 (Segmentation of 3D Visible Human Color Images by Balloon)

  • 김한영;김동성;강흥식
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
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    • pp.73-76
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    • 2001
  • A segmentation is a prior processing for medical image analysis and 3D reconstruction. This Paper provides the method to segment 3D Visible Human color images. Firstly, the reference images that have a initial curve are segmented using Balloon and the results are propagated to the adjacent images. In the propagation processing, the result of the adjacent slice is modified by Edge-limited SRG Finally, the 3D Balloon improves the segmentation results of each 2D slice. the proposed method's performance was verified through the experiments to segment thigh muscles of Visible Human color images.

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다시점 및 다중클러스터 환경에서 네트워크를 이용한 효율적인 실시간 영상 합성 기법 (An Efficient Real-Time Image Reconstruction Scheme using Network m Multiple View and Multiple Cluster Environments)

  • 유강수;임은천;심춘보
    • 한국정보통신학회논문지
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    • 제13권11호
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    • pp.2251-2259
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    • 2009
  • 네트워크를 기반으로 하나의 클러스터가 4개의 카메라로 구성된 4개의 다중 클러스터로부터 2D 영상을 조합하여 3D 입체 영상을 생성하는 알고리즘 및 시스템을 제안한다. 제안하는 기법은 다중 클러스터 환경에서 동작하고 실시간 대용량의 데이터 처리로 인한 시스템의 부하를 분산시키기 위해 네트워크를 이용한 서버-클라이언트 구조를 가진다. 아울러 성능 향상을 고려해 JPEG 압축과 램 디스크 방식을 적용한다. 4채널 16개의 카메라로부터 입력되는 입력 영상에 대해서 이진화 영상을 구하고, Sobel 및 Prewitt 등의 에지 검출 알고리즘을 적용시킨 후 영상들 간의 시차를 구한 후에 3D 입체 영상을 생성한다. 성능 분석 결과, 클라이언트에서 서버로 전송하는 전송시간은 약 0.05초가 소요되며, 4채널 16개의 카메라로부터 2D 영상을 조합하여 3D 입체 영상을 생성하는 알고리즘에 소요되는 시간은 약 0.84초가 소요된다. 이를 통해 실시간으로 다시점 및 다중 클러스터 환경에서 3D 입체 영상을 생성하는 효율적인 시스템임을 확인할 수 있었다.

다중센서 데이터를 이용한 구조물의 3차원 모델링 (The Three Dimensional Modeling Method of Structure in Urban Areas using Airborne Multi-sensor Data)

  • 손호웅;김기영;김영경
    • 지구물리
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    • 제9권1호
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    • pp.7-19
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    • 2006
  • Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

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선형적 위상배열 코일구조의 시뮬레이션을 통한 민감도지도의 공간 해상도 및 필터링 변화에 따른 MR-SENSE 영상재구성 평가 (Evaluation of MR-SENSE Reconstruction by Filtering Effect and Spatial Resolution of the Sensitivity Map for the Simulation-Based Linear Coil Array)

  • 이동훈;홍철표;한봉수;김형진;서재준;김소현;이춘형;이만우
    • 대한의용생체공학회:의공학회지
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    • 제32권3호
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    • pp.245-250
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    • 2011
  • Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

컴프턴 카메라를 위한 재배열 기반 확정론적 영상재구성법 (Rebinning-Based Deterministic Image Reconstruction Methods for Compton Camera)

  • 이미노;이수진;서희
    • 대한의용생체공학회:의공학회지
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    • 제32권1호
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    • pp.15-24
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    • 2011
  • While Compton imaging is recognized as a valuable 3-D technique in nuclear medicine, reconstructing an image from Compton scattered data has been of a difficult problem due to its computational complexity. The most complex and time-consuming computation in Compton camera reconstruction is to perform the conical projection and backprojection operations. To alleviate the computational burden imposed by these operations, we investigate a rebinning method which can convert conical projections into parallel projections. The use of parallel projections allows to directly apply the existing deterministic reconstruction methods, which have been useful for conventional emission tomography, to Compton camera reconstruction. To convert conical projections into parallel projections, a cone surface is sampled with a number of lines. Each line is projected onto an imaginary plane that is mostly perpendicular to the line. The projection data rebinned in each imaginary plane can then be treated as the standard parallel projection data. To validate the rebinning method, we tested with the representative deterministic algorithms, such as the filtered backprojection method and the algebraic reconstruction technique. Our experimental results indicate that the rebinning method can be useful when the direct application of existing deterministic methods is needed for Compton camera reconstruction.

Occluded Object Motion Estimation System based on Particle Filter with 3D Reconstruction

  • Ko, Kwang-Eun;Park, Jun-Heong;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제12권1호
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    • pp.60-65
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    • 2012
  • This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

딥러닝기반 입체 영상의 획득 및 처리 기술 동향 (Recent Technologies for the Acquisition and Processing of 3D Images Based on Deep Learning)

  • 윤민성
    • 전자통신동향분석
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    • 제35권5호
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    • pp.112-122
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    • 2020
  • In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

원추형 주사 방식의 3차원 영상 재구성(TTCR) 알고리즘 - 평행주사 방식(TTR) 알고리즘의 좌표변환 - (True Three-Dimensional Cone-Beam Reconstruction (TTCR) Algorithm - Transform Method from Parallel-beam (TTR) Algorithm -)

  • 이상지;나종범;조장희
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1989년도 춘계학술대회
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    • pp.55-59
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    • 1989
  • A true three-dimensional cone-beam reconstruction (TTCR) algorithm for the complete sphere geometry is derived, which is applicable to the direct volume image reconstruction from 2-D cone-beam projections. The algorithm is based on the modified filtered backprojection technique which uses a set of 2-D space-invariant filters and is derived from the previously developed parallel-beam true three-dimensional reconstruction(TTR) algorithm. The proposed algorithm proved to be superior in spatial resolution compared with the parallel-beam TTR algorithm.

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Position Detection of a Scattering 3D Object by Use of the Axially Distributed Image Sensing Technique

  • Cho, Myungjin;Shin, Donghak;Lee, Joon-Jae
    • Journal of the Optical Society of Korea
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    • 제18권4호
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    • pp.414-418
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    • 2014
  • In this paper, we present a method to detect the position of a 3D object in scattering media by using the axially distributed sensing (ADS) method. Due to the scattering noise of the elemental images recorded by the ADS method, we apply a statistical image processing algorithm where the scattering elemental images are converted into scatter-reduced ones. With the scatter-reduced elemental images, we reconstruct the 3D images using the digital reconstruction algorithm based on ray back-projection. The reconstructed images are used for the position detection of a 3D object in the scattering medium. We perform the preliminary experiments and present experimental results.

비선형 전변동을 이용한 초점거리 변화 기반의 3 차원 깊이 측정 방법 (3D Shape Recovery Using Image Focus through Nonlinear Total Variation)

  • 무하마드 타릭 마흐무드;최영규
    • 반도체디스플레이기술학회지
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    • 제12권2호
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    • pp.27-32
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    • 2013
  • Shape From Focus (SFF) is a passive optical technique to recover 3D structure of an object that utilizes focus information from 2D images of the object taken at different focus levels. Mostly, SFF methods use a single focus measure to compute image focus quality of each pixel in the image sequence. However, it is difficult to recover accurate 3D shape using a single focus measure, as different focus measures perform differently in diverse conditions. In this paper, a nonlinear Total Variation (TV) based approach is proposed for 3D shape recovery. To improve the result of surface reconstruction, several initial depth maps are obtained using different focus measures and the resultant 3D shape is obtained by diffusing them through TV. The proposed method is tested and evaluated by using image sequences of synthetic and real objects. The results and comparative analysis demonstrate the effectiveness of our method.