• 제목/요약/키워드: vision-based method

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바이프리즘 스테레오 시각 센서를 이용한 GMA 용접 비드의 3차원 형상 측정 (Measurement of GMAW Bead Geometry Using Biprism Stereo Vision Sensor)

  • 이지혜;이두현;유중돈
    • Journal of Welding and Joining
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    • 제19권2호
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    • pp.200-207
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    • 2001
  • Three-diemnsional bead profile was measured using the biprism stereo vision sensor in GMAW, which consists of an optical filter, biprism and CCD camera. Since single CCD camera is used, this system has various advantages over the conventional stereo vision system using two cameras such as finding the corresponding points along the horizontal scanline. In this wort, the biprism stereo vision sensor was designed for the GMAW, and the linear calibration method was proposed to determine the prism and camera parameters. Image processing techniques were employed to find the corresponding point along the pool boundary. The ism-intensity contour corresponding to the pool boundary was found in the pixel order and the filter-based matching algorithm was used to refine the corresponding points in the subpixel order. Predicted bead dimensions were in broad agreements with the measured results under the conditions of spray mode and humping bead.

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시스템 파라미터의 변동 하에서도 강건한 능동적인 비전의 시선 고정 (Robust Gaze-Fixing of an Active Vision System under Variation of System Parameters)

  • 한영모
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제1권3호
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    • pp.195-200
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    • 2012
  • 카메라의 시선을 조정하기 위해서는 비전 시스템의 시스템 파라미터를 사용해야 한다. 하지만 이러한 시스템 파라미터는 측정 당시와 사용중이 달라 질 수 있다. 이 경우 원하는 카메라의 시선 조정이 이루어지기 어렵다. 이 문제를 보완하기 위한 방법으로서 본 연구에서는 LMI(Linear Matrix Inequality)에 기반한 비전 시스템의 시스템 파라미터의 변화에 강건한 시선 고정 방법을 제안한다. 시뮬레이션 검증 결과는 제안하는 방법이 기존의 선형 알고리즘에 비해 더 적은 시선 추적 에러를 보이고, 기존의 비선형 알고리즘에 비해 더 안정적인 시선 추적 에러를 보인다. 또한 제안하는 방법은 속도가 빨라서 실시간 사용이 가능하다.

High Accuracy Vision-Based Positioning Method at an Intersection

  • Manh, Cuong Nguyen;Lee, Jaesung
    • Journal of information and communication convergence engineering
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    • 제16권2호
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    • pp.114-124
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    • 2018
  • This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

마스크 생산 라인에서 다중 영상 기반 마스크 이어링 검사 방법 (Multi-Vision-based Inspection of Mask Ear Loops Attachment in Mask Production Lines)

  • 우지명;이상현;이헌철
    • 대한임베디드공학회논문지
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    • 제17권6호
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    • pp.337-346
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    • 2022
  • This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.

A Vision-Based Method to Find Fingertips in a Closed Hand

  • Chaudhary, Ankit;Vatwani, Kapil;Agrawal, Tushar;Raheja, J.L.
    • Journal of Information Processing Systems
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    • 제8권3호
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    • pp.399-408
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    • 2012
  • Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

Deep Learning Machine Vision System with High Object Recognition Rate using Multiple-Exposure Image Sensing Method

  • Park, Min-Jun;Kim, Hyeon-June
    • 센서학회지
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    • 제30권2호
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    • pp.76-81
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    • 2021
  • In this study, we propose a machine vision system with a high object recognition rate. By utilizing a multiple-exposure image sensing technique, the proposed deep learning-based machine vision system can cover a wide light intensity range without further learning processes on the various light intensity range. If the proposed machine vision system fails to recognize object features, the system operates in a multiple-exposure sensing mode and detects the target object that is blocked in the near dark or bright region. Furthermore, short- and long-exposure images from the multiple-exposure sensing mode are synthesized to obtain accurate object feature information. That results in the generation of a wide dynamic range of image information. Even with the object recognition resources for the deep learning process with a light intensity range of only 23 dB, the prototype machine vision system with the multiple-exposure imaging method demonstrated an object recognition performance with a light intensity range of up to 96 dB.

3D Printed Flexible Cathode Based on Cu-EDTA that Prepared by Molecular Precursor Method and Microwave Processing for Electrochemical Machining

  • Yan, Binggong;Song, Xuan;Tian, Zhao;Huang, Xiaodi;Jiang, Kaiyong
    • Journal of Electrochemical Science and Technology
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    • 제11권2호
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    • pp.180-186
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    • 2020
  • In this work, a metal-ligand solution (Cu-EDTA) was prepared based on the molecular precursor method and the solution was spin-coated onto 3D printed flexible photosensitive resin sheets. After being processed by microwave, a laser with a wavelength of 355 nm was utilized to scan the spin-coated sheets and then the sheets were immersed in an electroless copper plating solution to deposit copper wires. With the help of microwave processing, the adhesion between copper wires and substrate was improved which should result from the increase of roughness, decrease of contact angle and the consistent orientation of coated film according to the results of 3D profilometer and SEM. XPS results showed that copper seeds formed after laser scanning. Using the 3D printed flexible sheets as cathode and galvanized iron as anode, electrochemical machining was conducted.

영상 내 건설인력 위치 추적을 위한 등극선 기하학 기반의 개체 매칭 기법 (Entity Matching for Vision-Based Tracking of Construction Workers Using Epipolar Geometry)

  • 이용주;김도완;박만우
    • 한국BIM학회 논문집
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    • 제5권2호
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    • pp.46-54
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    • 2015
  • Vision-based tracking has been proposed as a means to efficiently track a large number of construction resources operating in a congested site. In order to obtain 3D coordinates of an object, it is necessary to employ stereo-vision theories. Detecting and tracking of multiple objects require an entity matching process that finds corresponding pairs of detected entities across the two camera views. This paper proposes an efficient way of entity matching for tracking of construction workers. The proposed method basically uses epipolar geometry which represents the relationship between the two fixed cameras. Each pixel coordinate in a camera view is projected onto the other camera view as an epipolar line. The proposed method finds the matching pair of a worker entity by comparing the proximity of the all detected entities in the other view to the epipolar line. Experimental results demonstrate its suitability for automated entity matching for 3D vision-based tracking of construction workers.

로봇 축구 대회를 위한 영상 처리 시스템 (A Vision System for ]Robot Soccer Game)

  • 고국원;최재호;김창효;김경훈;김주곤;이수호;조형석
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 추계학술대회 논문집
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    • pp.434-438
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    • 1996
  • In this paper we present the multi-agent robot system and the vision system developed for participating in micro robot soccer tournament. The multi-agent robot system consists of micro robot, a vision system, a host computer and a communication module. Micro robot are equipped with two mini DC motors witf encoders and gearboxes, a R/F receiver, a CPU and infrared sensors for obstacle detection. A vision system is used to recognize the position of the ball and opponent robots, position and orientation of our robots. The vision system is composed of a color CCD camera and a vision processing unit(AISI vision computer). The vision algorithm is based on morphological method. And it takes about 90 msec to detect ball and 3-our robots and 3-opponent robots with reasonable accuracy

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Real-Time Pipe Fault Detection System Using Computer Vision

  • Kim Hyoung-Seok;Lee Byung-Ryong
    • International Journal of Precision Engineering and Manufacturing
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    • 제7권1호
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    • pp.30-34
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    • 2006
  • Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.