• Title, Summary, Keyword: visual estimation method

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

  • Ko, Dong-Min;Choi, Kang-Sun
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.3
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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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Traffic Estimation Method for Visual Sensor Networks (비쥬얼 센서 네트워크에서 트래픽 예측 방법)

  • Park, Sang-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.11
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    • pp.1069-1076
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    • 2016
  • Recent development in visual sensor technologies has encouraged various researches on adding imaging capabilities to sensor networks. Video data are bigger than other sensor data, so it is essential to manage the amount of image data efficiently. In this paper, a new method of video traffic estimation is proposed for efficient traffic management of visual sensor networks. In the proposed method, a first order autoregressive model is used for modeling the traffic with the consideration of the characteristics of video traffics acquired from visual sensors, and a Kalman filter algorithm is used to estimate the amount of video traffics. The proposed method is computationally simple, so it is proper to be applied to sensor nodes. It is shown by experimental results that the proposed method is simple but estimate the video traffics exactly by less than 1% of the average.

A study on the quantitation of asbestos by the visual estimation and point counting method (시야평가법과 포인트계수법에 의한 석면정량평가 연구)

  • Choi, Yun-Ho;Kim, Tae-Hwa;Bae, Yong-Soo;Kim, Tae-Hyun;Kim, Hyeon-Ja;Jang, Eun-Ah;Hwang, Beom-Goo
    • Analytical Science and Technology
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    • v.27 no.3
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    • pp.153-160
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    • 2014
  • While variety of cases of studies about asbestos analysis methods are released internationally, the results of Asbestos Containing Materials (ACM) according to differences in the method of the analysis is becoming an issue. In this study, homogeneity ensured ACM samples were analyzed by visual estimation method and point counting method, and the result cound be used not only to improve the reliability on asbestos analysis of the institutions and analysts but also to obtain the basic data of Polarizing Light Microscope (PLM) analysis by comparing and evaluating. Asbestos analysis were divided into qualitative and quantitative analysis method. The quantitative analysis was performed by visual estimation method and point counting method (total 400 points) of EPA 600-R-93-116 method by using PLM. Firstly, The following was the result of homogeneity of the samples by ANOVA (Analysis of variance) and the results were satisfied. The results of qualitative analysis showed that the samples were chrysotile and amosite, and about the results of quantitative analysis, asbestos concentration determined by point counting method tend to be lower than concentrations determined by visual estimation method and also, pont counting method was a little more complicated and time-consuming.

A Study on the Visual Effect of Landscape on Window in Living Space (주택 창에서 조망의 시각적 효과에 관한 연구)

  • Kim Hye-Young
    • Journal of the Korean housing association
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    • v.15 no.4
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    • pp.17-23
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    • 2004
  • The purpose of this study is to grasp visual effects of landscape on window in living space. The visual effects in the 1/3 living room scale models that are different in the dimension of window, the place of window and the landscape through the window is judge using a method of magnitude estimation. In consequence of these experiment, the following results were obtained. 1) The brightness influences the evaluation marks on visual effects of window on living space. 2) The existence of landscape has an effect on a sense of extent for living space. 3) The existence of window in visual field makes a great difference to the visual effects.

A Camera Pose Estimation Method for Rectangle Feature based Visual SLAM (사각형 특징 기반 Visual SLAM을 위한 자세 추정 방법)

  • Lee, Jae-Min;Kim, Gon-Woo
    • The Journal of Korea Robotics Society
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    • v.11 no.1
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    • pp.33-40
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    • 2016
  • In this paper, we propose a method for estimating the pose of the camera using a rectangle feature utilized for the visual SLAM. A warped rectangle feature as a quadrilateral in the image by the perspective transformation is reconstructed by the Coupled Line Camera algorithm. In order to fully reconstruct a rectangle in the real world coordinate, the distance between the features and the camera is needed. The distance in the real world coordinate can be measured by using a stereo camera. Using properties of the line camera, the physical size of the rectangle feature can be induced from the distance. The correspondence between the quadrilateral in the image and the rectangle in the real world coordinate can restore the relative pose between the camera and the feature through obtaining the homography. In order to evaluate the performance, we analyzed the result of proposed method with its reference pose in Gazebo robot simulator.

1-Point Ransac Based Robust Visual Odometry

  • Nguyen, Van Cuong;Heo, Moon Beom;Jee, Gyu-In
    • Journal of Positioning, Navigation, and Timing
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    • v.2 no.1
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    • pp.81-89
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    • 2013
  • Many of the current visual odometry algorithms suffer from some extreme limitations such as requiring a high amount of computation time, complex algorithms, and not working in urban environments. In this paper, we present an approach that can solve all the above problems using a single camera. Using a planar motion assumption and Ackermann's principle of motion, we construct the vehicle's motion model as a circular planar motion (2DOF). Then, we adopt a 1-point method to improve the Ransac algorithm and the relative motion estimation. In the Ransac algorithm, we use a 1-point method to generate the hypothesis and then adopt the Levenberg-Marquardt method to minimize the geometric error function and verify inliers. In motion estimation, we combine the 1-point method with a simple least-square minimization solution to handle cases in which only a few feature points are present. The 1-point method is the key to speed up our visual odometry application to real-time systems. Finally, a Bundle Adjustment algorithm is adopted to refine the pose estimation. The results on real datasets in urban dynamic environments demonstrate the effectiveness of our proposed algorithm.

Fast Motion Estimation Technique using Efficient Prediction of Motion Vectors (움직임 벡터의 효율적 예측을 이용한 고속 움직임 추정 기법)

  • Kim, Jongho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.945-949
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    • 2009
  • This paper proposes an enhanced motion estimation that is one of core parts affecting the coding performance and visual quality in video coding. Although the full search technique, which is the most basic method of the motion estimation, presents the best visual quality, its computational complexity is great, since the search procedures to find the best matched block with each block in the current frame are carried out for all points inside the search area. Thus, various fast algorithms to reduce the computational complexity and maintain good visual quality have been proposed. The PMVFAST adopted the MPEG-4 visual standard produces the visual quality near that by the full search technique with the reduced computational complexity. In this paper, we propose a new motion vector prediction method using median processing. The proposed method reduces the computational complexity for the motion estimation significantly. Experimental results show that the proposed algorithm is faster than the PMVFAST and better than the full search in terms of search speed and average PSNR, respectively.

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Edge-Preserving and Adaptive Transmission Estimation for Effective Single Image Haze Removal

  • Kim, Jongho
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.21-29
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    • 2020
  • This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

Image-based Visual Servoing Through Range and Feature Point Uncertainty Estimation of a Target for a Manipulator (목표물의 거리 및 특징점 불확실성 추정을 통한 매니퓰레이터의 영상기반 비주얼 서보잉)

  • Lee, Sanghyob;Jeong, Seongchan;Hong, Young-Dae;Chwa, Dongkyoung
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.6
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    • pp.403-410
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    • 2016
  • This paper proposes a robust image-based visual servoing scheme using a nonlinear observer for a monocular eye-in-hand manipulator. The proposed control method is divided into a range estimation phase and a target-tracking phase. In the range estimation phase, the range from the camera to the target is estimated under the non-moving target condition to solve the uncertainty of an interaction matrix. Then, in the target-tracking phase, the feature point uncertainty caused by the unknown motion of the target is estimated and feature point errors converge sufficiently near to zero through compensation for the feature point uncertainty.