• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.156-162
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• 2007

The parallel beam SPECT system acquires projection data by using collimators in conjunction with photon detectors. The projection data of the parallel beam SPECT system is, however, blurred by the point response function of the collimator that is used to define the range of directions where photons can be detected. By increasing the number of parallel holes per unit area in collimator, one can reduce such blurring effect. This approach also, however, has the blurring problem if the distance between the object and the collimator becomes large. In this paper we consider correction methods for artifacts caused by non-circular orbit of parallel beam SPECT with many parallel holes per detector cell. To do so, we model the relationship between the object and its projection data as a linear system, and propose an iterative reconstruction method including artifacts correction. We compute the projector and the backprojector, which are required in iterative method, as a sum of convolutions with distance-dependent point response functions instead of matrix form, where those functions are analytically computed from a single function. By doing so, we dramatically reduce the computation time and memory required for the generation of the projector and the backprojector. We conducted several simulation studies to compare the performance of the proposed method with that of conventional Fourier method. The result shows that the proposed method outperforms Fourier methods objectively and subjectively.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1
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• pp.49-54
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• 1998

본 논문에서는 잡음이 존재하는 환경에 강인한 것으로 알려져 있는 투영 방법을 우 도 측정에 가중 함수와 결합하여 사용하는 방법을 제안하였다. 반연속 HMM을 이용한 고립 단어의 인식 실험 결과, 제안한 방법이 실험에 사용된 잡음의 환경들에서 모두 좋은 성능을 나타내었다. 아울러 병렬 모델 결합 방법을 반연속 HMM에 적용하였는데 이는 코드북의 변 환반으로 쉽게 잡음의 특성을 반영할 수 있다. 가중 투영 우도 측정 방법을 병렬 모델 결합 방법에 적용한 경우에도 우수한 성능을 거둘 수 있었다.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.117-123
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• 2012

Many nations have been launched their own earth observation satellites due to much interest in space exploration. Because of this, the number of high resolution satellite are increasing day by day. With the development of web environment, general users have easy access to satellite images. The research conducted a basic study about web-based satellite photogrammetry in order to determine three dimensional coordinates easily without having profound knowledge of satellite sensor modeling. Various element technologies were analyzed to decide three dimensional coordinates by using high resolution satellite images in web environment, and case studies were conducted by using IKONOS satellite images. By applying parallel projection model, which is one of sensor modeling methods, epipolar image was created and prototype form of program that can decide three dimensional location in web environment was implemented. Through this, general users could decide three dimensional location easily in web environment and knew that already existed spatial information can be renewed and used in service area.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.5
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• pp.443-450
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• 2009

Purpose: Conventional image reconstruction uses simplified physical models of projection. However, real physics, for example 3D reconstruction, takes too long time to process all the data in clinic and is unable in a common reconstruction machine because of the large memory for complex physical models. We suggest the realistic distributed memory model of fast-reconstruction using parallel processing on personal computers to enable large-scale technologies. Materials and Methods: The preliminary tests for the possibility on virtual manchines and various performance test on commercial super computer, Tachyon were performed. Expectation maximization algorithm with common 2D projection and realistic 3D line of response were tested. Since the process time was getting slower (max 6 times) after a certain iteration, optimization for compiler was performed to maximize the efficiency of parallelization. Results: Parallel processing of a program on multiple computers was available on Linux with MPICH and NFS. We verified that differences between parallel processed image and single processed image at the same iterations were under the significant digits of floating point number, about 6 bit. Double processors showed good efficiency (1.96 times) of parallel computing. Delay phenomenon was solved by vectorization method using SSE. Conclusion: Through the study, realistic parallel computing system in clinic was established to be able to reconstruct by plenty of memory using the realistic physical models which was impossible to simplify.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.57-59
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• 2003

Digital surface model generation from IKONOS stereo imagery is a new challenge in photogrammetric community, especially when the satellite company does not provide the raw data as well as their ancillary ephemeris data. In this paper we utilized an estimated relief displacement azimuth and the nominal collection elevation data included in the metadata file to correct the relief displacement of GCPs, together with a linear transformation for geometric modeling of IKONOS imagery. Space intersection is performed by the trigonometric intersection assuming a parallel projection of IKONOS imagery due to its small FOV and frame size. In the experiment, less than 2-meters of RMSE in orbit modeling is achieved denoting the potential positioning accuracy of the IKONOS stereo imagery.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1885-1888
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• 2004

In order to render 3D model of the bone, the stack of cross-sectional images must be reconstructed from a series of X-ray radiographs, served as the projections. In the case where the distance between x-ray source and detector is not infinite, image reconstruction from projection based on parallel-beam geometry provides an error in the cross-sectional image. In such case, image reconstruction from projection based on conebeam geometry must be exercised instead. This paper is devoted to the determination of detector center for SART conebeam Technique which is critically effect the performance of the resulting 3D modeling.

• Journal of electromagnetic engineering and science
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• v.10 no.3
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• pp.166-170
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• 2010

To numerically calculate electromagnetic scattering from the electrical-large three-dimensional(3D) objects, the high-frequency approaches have been usually applied, but the accuracy and feasibility of these geometrical and physical optics(GO-PO) approaches, to some extent, are remained to be improved. In this paper, a new framework is developed for calculation of the near-field scattering field of an electrical-large 3D target by using a multilevel fast multipole algorithm(MLFMA) and generation of radar images by using a fast back-projection(FBP) algorithm. The MPI(Message Passing Interface) parallel computing is carried out to multiply the calculation efficiency greatly. Finally, a simple example of perfectly electrical conducting(PEC) patch and a canonical case of Fighting Falcon F-16 are presented.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.652-655
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• 2004

The geometry of satellite image captured by linear pushbroom scanner is different from that of frame camera image. Since the exterior orientation parameters for satellite image will vary scan line by scan line, the epipolar geometry of satellite image differs from that of frame camera image. As we know, 2D affine orientation for the epipolar image of linear pushbroom scanners system are well-established by using the collinearity equation (Testsu Ono, 1999). Also, another epipolar geometry of linear pushbroom scanner system is recently established by Habib(2002). He reported that the epipolar geometry of linear push broom satellite image is realized by parallel projection based on 2D affine models. Here, in this paper, we compared the Ono's method with Habib's method. In addition, we proposed a method that generates epipolar resampled images. For the experiment, IKONOS stereo images were used in generating epipolar images.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Advances in robotics research
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• v.1 no.1
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• pp.81-99
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• 2014

This paper contributes towards the development of a computer vision system for telemonitoring of industrial articulated robotic arms. The system aims to provide precision real time measurements of the joint angles by employing low cost cameras and visual markers on the body of the robot. To achieve this, a mathematical model that connects image features and joint angles was developed covering rotation of a single joint whose axis is parallel to the visual projection plane. The feature that is examined during image processing is the varying area of given circular target placed on the body of the robot, as registered by the camera during rotation of the arm. In order to distinguish between rotation directions four targets were used placed every $90^{\circ}$ and observed by two cameras at suitable angular distances. The results were deemed acceptable considering camera cost and lighting conditions of the workspace. A computational error analysis explored how deviations from the ideal camera positions affect the measurements and led to appropriate correction. The method is deemed to be extensible to multiple joint motion of a known kinematic chain.