• 제목/요약/키워드: Position of Corner

검색결과 120건 처리시간 0.026초

웨이퍼 다이 위치 인식을 위한 명암 영상 코너점 검출 (Comer Detection in Gray Lavel Images for Wafer Die Position Recognition)

  • 나재형;오해석
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권6호
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    • pp.792-798
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    • 2004
  • 본 논문에서는 웨이퍼 영상에서 다이 위치를 인식하기 위한 새로운 코너점 검출 방법을 제안한다. 웨이퍼 다이 위치 인식은 WSCSP(Wafer Scale Chip Scale Packaging)기술에 필수적인 과정으로서 웨이퍼 윗면의 다이 패턴을 얼마나 정확히 인식하느냐에 따라서 후 공정의 정확도가 결정된다. 본 논문에서는 정확한 다이 위치를 인식하기 위하여 계층적 명암 영상 코너 검출 방법을 제안한다. 새로운 코너 검출자는 코너 영역을 마스크 크기에 따라서 동심원으로 나누어 각각의 동심원에서의 코너성과 방향성을 구하여 정확한 코너점을 검출하도록 하였다. 또한 계층적 구조를 가지고 처리하여 기존의 명암 영상코너 검출자 보다 더 빠른 처리 속도를 얻을 수 있도록 하였다.

랜덤하프변환과 코너추출을 이용한 경사면의 장애물 위치 탐색 (Obstacle Position Detection on an Inclined Plane Using Randomized Hough Transform and Corner Detection)

  • 황선민;이민철
    • 제어로봇시스템학회논문지
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    • 제17권5호
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    • pp.419-428
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    • 2011
  • This paper suggests a judgement method for an inclined plane before entrance of it and the detection of obstacle position. Main idea is started from the assumption that obstacle is always on the bottom plane, and corner appears at this position. The process to detect the obstacle consists of three steps. First the 3D data using stereo matching is acquired to detect an obstacle. Second a bottom plane is extracted by using limit condition. Last the obstacle position is found by using Harris corner detection. Obstacle position detection on an inclined plane was verified by outdoor and indoor experiment. In error analysis, it is confirmed that an average error of obstacle detection in outdoor was larger than the error in indoor but the error are within about 0.030 m. This method will be applied to unmanned vehicles to navigate under various environment.

레이저 코너 패턴의 매칭을 이용한 이동 로봇의 EKF 기반 SLAM (EKF-based Simultaneous Localization and Mapping of Mobile Robot using Laser Corner Pattern Matching)

  • 김태형;박태형
    • 전기학회논문지
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    • 제65권12호
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    • pp.2094-2102
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    • 2016
  • In this paper, we propose an extended Kalman filter(EKF)-based simultaneous localization and mapping(SLAM) method using laser corner pattern matching for mobile robots. SLAM is one of the most important problems of mobile robot. However, existing method has the disadvantage of increasing the computation time, depending on the number of landmarks. To improve computation time, we produce the corner pattern using classified and detected corner points. After producing the corner patterns, it is estimated that mobile robot's global position by matching them. The estimated position is used as measurement model in the EKF. To evaluated proposed method, we preformed the experiments in the indoor environments. Experimental results of proposed method are shown to maintain an accuracy and decrease the computation time.

SMD 및 PCB의 방향과 위치 탐지 (Detection of Orientation and Position of the SMD and PCB)

  • 정홍규;박래홍
    • 전자공학회논문지B
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    • 제31B권3호
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    • pp.80-90
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    • 1994
  • In this paper, a high-resolution algorithm for detecting the orientation and position of the SMD and an algorithm for compensating the position and skew angle of the PCB are proposed. The proposed algorithm for the first topic consists of two parts. Its first part is a preprocessing step. in which corner points of the SMD are detected and they are grouped. Then the coarse angle of the principal axis is obtained by line fitting. The second part is a main processing step, in which the fuzzy Hough transform over the limited range of angles is applied to the corner points to detect precisely the orientation of the SMD. The position of the SMD is determined by using its four corner points. The proposed algorithm for the second topic is the one which detects a rotation angle and translation parameters of the PCB using a template matching method. The computer simulation shows that the parametes obtained by proposed algorithms are more precise than those by the several conventional methods considered. The proposed algorithms can be applied to the fast and accurate automatic inspection systems.

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Precise Vehicle Localization Using 3D LIDAR and GPS/DR in Urban Environment

  • Im, Jun-Hyuck;Jee, Gyu-In
    • Journal of Positioning, Navigation, and Timing
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    • 제6권1호
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    • pp.27-33
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    • 2017
  • GPS provides the positioning solution in most areas of the world. However, the position error largely occurs in the urban area due to signal attenuation, signal blockage, and multipath. Although many studies have been carried out to solve this problem, a definite solution has not yet been proposed. Therefore, research is being conducted to solve the vehicle localization problem in the urban environment by converging sensors such as cameras and Light Detection and Ranging (LIDAR). In this paper, the precise vehicle localization using 3D LIDAR (Velodyne HDL-32E) is performed in the urban area. As there are many tall buildings in the urban area and the outer walls of urban buildings consist of planes generally perpendicular to the earth's surface, the outer wall of the building meets at a vertical corner and this vertical corner can be accurately extracted using 3D LIDAR. In this paper, we describe the vertical corner extraction method using 3D LIDAR and perform the precise localization by combining the extracted corner position and GPS/DR information. The driving test was carried out in an about 4.5 km-long section near Teheran-ro, Gangnam. The lateral and longitudinal RMS position errors were 0.146 m and 0.286 m, respectively and showed very accurate localization performance.

2D 비젼 센서를 이용한 차체의 3D 자세측정 (The Position Estimation of a Car Using 2D Vision Sensors)

  • 한명철;김정관
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 추계학술대회 논문집
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    • pp.296-300
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    • 1996
  • This paper presents 3D position estimation algorithm with the images of 2D vision sensors which issues Red Laser Slit light and recieves the line images. Since the sensor usually measures 2D position of corner(or edge) of a body and the measured point is not fixed in the body, the additional information of the corner(or edge) is used. That is, corner(or edge) line is straight and fixed in the body. For the body which moves in a plane, the Transformation matrix between the body coordinate and the reference coordinate is analytically found. For the 3D motion body, linearization technique and least mean squares method are used.

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Fatigue performance of rib-roof weld in steel bridge decks with corner braces

  • Fu, Zhongqiu;Ji, Bohai;Wang, Yixun;Xu, Jie
    • Steel and Composite Structures
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    • 제26권1호
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    • pp.103-113
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    • 2018
  • To study the effects of corner braces on fatigue performance of the U-rib and roof weld in steel bridge decks, the fatigue experiment was carried out to compare characteristics of the crack shape with and without corner braces. The improvement of fatigue life and stress variation after setting corner braces were also analysed. Different parameters of corner brace sizes, arrangements, and detail types were considered in the FEM models to obtain stress distribution and variation at the weld. Furthermore, enhancement of the fatigue performance by corner braces was evaluated. The results demonstrated that the corner brace could improve the fatigue life of the U-rib and roof weld, which exerted even no influence on the crack shape. Moreover, stress of the roof weld was decreased and the crack position was transferred from the root weld to U-rib and corner brace weld. It was suggested no weld scallop should be drilled on the corner brace. A transverse rib with lower height which was set between U-ribs was favourable for improvement of fatigue performance.

고정밀 머신 비전을 위한 정확한 PCB 윤곽선과 코너 검출 (Accurate PCB Outline Extraction and Corner Detection for High Precision Machine Vision)

  • 고동민;최강선
    • 반도체디스플레이기술학회지
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    • 제16권3호
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    • pp.53-58
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    • 2017
  • Recently, advance in technology have increased the importance of visual inspection in semiconductor inspection areas. In PCB visual inspection, accurate line estimation is critical to the accuracy of the entire process, since it is utilized in preprocessing steps such as calibration and alignment. We propose a line estimation method that is differently weighted for the line candidates using a histogram of gradient information, when the position of the initial approximate corner points is known. Using the obtained line equation of the outline, corner points can be calculated accurately. The proposed method is compared with the existing method in terms of the accuracy of the detected corner points. The proposed method accurately detects corner points even when the existing method fails. For high-resolution frames of 3.5mega-pixels, the proposed method is performed in 89.01ms.

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2-D 슬리트광 비젼 센서를 이용한 물체의 자세측정 (The Position Estimation of a Body Using 2-D Slit Light Vision Sensors)

  • 김정관;한명철
    • 한국정밀공학회지
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    • 제16권12호
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    • pp.133-142
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    • 1999
  • We introduce the algorithms of 2-D and 3-D position estimation using 2-D vision sensors. The sensors used in this research issue red laser slit light to the body. So, it is very convenient to obtain the coordinates of corner point or edge in sensor coordinate. Since the measured points are normally not fixed in the body coordinate, the additional conditions, that corner lines or edges are straight and fixed in the body coordinate, are used to find out the position and orientation of the body. In the case of 2-D motional body, we can find the solution analytically. But in the case of 3-D motional body, linearization technique and least mean squares method are used because of hard nonlinearity.

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천장 조명의 위치와 방위 정보를 이용한 모노카메라와 오도메트리 정보 기반의 SLAM (Monocular Vision and Odometry-Based SLAM Using Position and Orientation of Ceiling Lamps)

  • 황서연;송재복
    • 제어로봇시스템학회논문지
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    • 제17권2호
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    • pp.164-170
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    • 2011
  • This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.