• 한국의학물리학회지:의학물리
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• 제26권1호
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• pp.18-27
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• 2015

컴프턴 산란 현상을 이용하여 전자적 집속 방법으로 영상화하는 컴프턴카메라는 고민감도 및 고에너지 해상도의 장점을 이용하여 핵의학 응용분야에 대한 잠재력이 큰 영상 시스템이다. 본 논문에서는 컴프턴카메라를 이용한 다중 추적자 영상의 효용성 평가와 정확한 3차원 단면영상 촬영을 위한 Orlov 조건을 만족하는 회전하는 컴프턴카메라의 구조를 조사하였다. 140/511 keV의 방사선원의 소프트웨어 모형을 구성하고 이에 대한 몬테카를로 전산모사 시뮬레이션을 수행하여 리스트모드 배열된 부분집합 기댓값 최대화 방법으로 재구성된 다중 추적자 영상으로 컴프턴카메라의 효용성을 검증하였다. 산란부와 흡수부를 평행하게 위치시킨 고정된 컴프턴카메라와 촬영대상 주위 $360^{\circ}$를 회전하는 컴프턴카메라를 구성하여 검출된 투사선의 구좌표계 각도에 대한 히스토그램을 비교 평가하였다. 140/511 keV의 동시 계측된 몬테카를로 전산모사 데이터의 다중 추적자 영상이 2차원 및 3차원 재구성 시 잘 구분되는 것을 확인하였으며, 회전된 컴프턴카메라의 경우, 회전각도에 반비례하여 3차원 영상재구성에 필요한 유효 투사선이 증가하였다. 26분의 계산 시간 및 5백만개의 적절한 유효 투사선의 개수를 고려할 때 컴프턴카메라의 회전각은 $30^{\circ}$가 현실적으로 적절할 것이며 증가한 검출 시간은 다중 컴프턴카메라를 구성하여 해결할 수 있다. 본 논문에서 고찰한 고민감도 및 고에너지 해상도를 가진 컴프턴 카메라는 다중추적자 영상화를 위해 적합한 시스템이며 생화학 및 생리학적 상태 변화에 대한 임상 정보를 제공하며 각종 질병 진단 및 치료 방법 개발 등에 기여할 수 있는 잠재력이 있는 영상 시스템이다.

• International Journal of Precision Engineering and Manufacturing
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• 제5권1호
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• 한국컴퓨터정보학회논문지
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• 제23권1호
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• 한국산업융합학회 논문집
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• 제22권4호
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5481-5495
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• 2018

Single pixel imaging technology has developed for years, however the video acquisition on the single pixel camera is not a well-studied problem in computer vision. This work proposes a new scheme for single pixel camera to acquire video data and a new regularization for robust signal recovery algorithm. The method establishes a single pixel video compressive sensing scheme to reconstruct the video clips in spatial domain by recovering the difference of the consecutive frames. Different from traditional data acquisition method works in transform domain, the proposed scheme reconstructs the video frames directly in spatial domain. At the same time, a new regularization called spatial cluster is introduced to improve the performance of signal reconstruction. The regularization derives from the observation that the nonzero coefficients often tend to be clustered in the difference of the consecutive video frames. We implement an experiment platform to illustrate the effectiveness of the proposed algorithm. Numerous experiments show the well performance of video acquisition and frame reconstruction on single pixel camera.

• 한국멀티미디어학회논문지
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• 제24권11호
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• pp.1518-1525
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• 2021

Due to the growth of VR industry and rise of digital twin industry, the importance of implementing 3D data same as real space is increasing. However, the fact that it requires expertise personnel and huge amount of time is a problem. In this paper, we propose a system that generates point cloud data with same shape and color as a real space, just by scanning the space. The proposed system integrates 3D geometric information from lidar and color information from stereo camera into one point cloud. Since the number of 3D points generated by lidar is not enough to express a real space with good quality, some of the pixels of 2D image generated by camera are mapped to the correct 3D coordinate to increase the number of points. Additionally, to minimize the capacity, overlapping points are filtered out so that only one point exists in the same 3D coordinates. Finally, 6DoF pose information generated from lidar point cloud is replaced with the one generated from camera image to position the points to a more accurate place. Experimental results show that the proposed system easily and quickly generates point clouds very similar to the scanned space.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.480-485
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• 2002

The purpose of this paper is the development of guidance algorithm for a mobile robot which is used to acquire the position and state information of the pipe defects such as crack, damage and through hole. The data used for the algorithm is the range data obtained by the range sensor which is based on an optical triangulation method. The sensor, which consists of a laser slit beam and a CCD camera, measures the 3D profile of the pipe's inner surface. After setting the range sensor on the robot, the robot is put into a pipe. While the camera and the LSB sensor part is rotated about the robot axis, a laser slit beam (LSB) is projected onto the inner surface of the pipe and a CCD camera captures the image. From the images the range data is obtained with respect to the sensor coordinate through a series of image processing and applying the sensor matrix. After the data is transformed into the robot coordinate, the position and orientation of the robot should be obtained in order to guide the robot. In addition, analyzing the data, 3D shape of the pipe is constructed and the numerical data for the defects of the pipe can be found. These data will be used for pipe maintenance and service.

• 스마트미디어저널
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• 제2권1호
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• pp.42-47
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• 2013

본 논문은 선박 네비게이션 단말기의 효율성을 위한 VDR 시스템 및 이를 이용한 데이터 출력 저장 방법에 관한 것으로, 압축된 디지털 데이터와 아날로그 영상을 카메라로부터 함께 출력할 수 있도록 함으로써 압축된 디지털 데이터는 VDR 장치의 영상 저장에 이용하고 아날로그 영상은 실시간으로 화면 출력에 이용할 수 있도록 하여, 네비게이션 단말기에 부하를 주지 않고 영상을 실시간으로 모니터로 출력함과 함께 SD 메모리에 저장하게 하는 VDR 장치 및 이률 이용한 데이터 출력 저장 등의 제어방법을 제시하고자 한다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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• pp.1504-1507
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• 2007

Depth data for is very important data for 3D display. Disparity and depth data makes users to feel 3D effect. We used stereo camera to measure depth and made fast algorithm to get in real time. This vision system can be substituted for expensive laser system.

• Journal of Positioning, Navigation, and Timing
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• 제9권2호
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• pp.131-138
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• 2020

In this paper, we analyze the delay phenomenon that can occur when controlling an unmanned aerial vehicle using a camera and describe a solution to solve the phenomenon. The group of pictures (GOP) value is changed in order to reduce the delay according to the frame data size that can occur in the moving image data transmission. The appropriate GOP values were determined through experimental data accumulation and validated through camera self-test, system integration laboratory (SIL) verification test and system integration test.