• Title/Summary/Keyword: Captured Image

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Monochromatic Image Analysis of Elastohydrodynamic Lubrication Film Thickness by Fringe Intensity Computation

  • Jang, Siyoul
    • Journal of Mechanical Science and Technology
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    • v.17 no.11
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    • pp.1704-1713
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    • 2003
  • Point contact film thickness in elastohydrodynamic lubrication (EHL) is analyzed by image processing method for the images from an optical interferometer with monochromatic incident light. Interference between the reflected lights both on half mirror Cr coating of glass disk and on super finished ball makes circular fringes depending on the contact conditions such as sliding velocity, applied load, viscosity-pressure characteristics and viscosity of lubricant under ambient pressure. In this situation the film thickness is regarded as the difference of optical paths between those reflected lights, which make dark and bright fringes with monochromatic incident light. The film thickness is computed by numbering the dark and bright fringe orders and the intensity (gray scale image) in each fringe regime is mapped to the corresponding film thickness. In this work, we developed a measuring technique for EHL film thickness by dividing the image patterns into two typical types under the condition of monochromatic incident light. During the image processing, the captured image is converted into digitally formatted data over the contact area without any loss of the image information of interferogram and it is also interpreted with consistency regardless of the observer's experimental experience. It is expected that the developed image processing method will provide a valuable basis to develop the image processing technique for color fringes, which is generally used for the measurement of relatively thin films in higher resolution.

The Faulty Detection of COG Using Image Subtraction (이미지 정합을 이용한 COG 불량 검출)

  • Joo, Ki-See
    • Proceedings of KOSOMES biannual meeting
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    • 2005.11a
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    • pp.203-208
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    • 2005
  • The CGO (Chip on Glass) to be measured a few micro unit is captured by line scan camera for the accuracy of chip inspection. But it is very sensitive to scan speed and lighting conditions. In this paper, we propose the methods to increase the accuracy of faulty detection by image subtraction. Image subtraction is detected faultiness by subtracting the image of a ' perfect ' COG from trot of the sample under tests. For image subtraction to be successful, the two images must be pre챠sely registered The two images is registered by the area segmentation pattern matching, and the result image get by operating the gradient mask image and the image to practice subtraction. A series of experimentation showed that the proposed algorithm shows substantial improvement over the other image subtraction methods.

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Algorithm to Estimate Oil Spill Area Using Digital Properties of Image

  • Jang, Hye-Jin;Nam, Jong-Ho
    • Journal of Ocean Engineering and Technology
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    • v.34 no.1
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    • pp.46-54
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    • 2020
  • Oil spill accidents at sea result in a wide range of damages, including the destruction of ocean environments and ecosystems, as well as human illnesses by the generation of harmful gases caused by phase changes in crude oil. When an oil spill occurs, an immediate initial action should be performed to minimize the potential damage. Existing studies have attempted to identify crude oil spillage by calculating the crude oil spill range using synthetic aperture radar (SAR) satellite images. However, SAR cannot capture rapidly evolving events because of its low acquisition frequency. Herein, an algorithm for estimating an oil spill area from an image obtained using a digital camera is proposed. Noise that may occur in the image when it is captured is first eliminated by preprocessing, and then the image is analyzed. After analyzing the characteristics of the digital image, a strategy to binarize an image using the color, saturation, or lightness contained in it is adopted. It is found that the oil spill area can be readily estimated from a digital image, allowing for a faster analysis than any conventional method. The usefulness of the oil spill area measurement was confirmed by applying the developed algorithm to various oil spill images.

Distortion Correction of Boundary Lines in a Tunnel Image Captured by Fisheye Lens (어안렌즈 터널영상의 경계선 왜곡 보정)

  • Kim, Gi-Hong;Jeong, Soo
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.55-63
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    • 2011
  • Having a wide angle of view, a fisheye lens is useful for obtaining images of the inside wall of a tunnel. A circular fisheye tunnel image can be transformed into a familiar rectangular image by applying the concept of cylindrical projection. This projection transformation causes several types of distortions in the projected image. This paper discusses the distortion on the boundary lines between smoothly curved wall and flat ground. We analyzed the cause of this boundary distortion, developed transformation model, and derived a correction formular. A distortion correction software programmed in Visual C++ applied to projected image. Consequently, boundary-corrected image could be obtained. Research into other distortions of projected image will helpful in obtaining tunnel image that resembles real tunnel from fisheye tunnel image.

An Algorithm for a pose estimation of a robot using Scale-Invariant feature Transform

  • Lee, Jae-Kwang;Huh, Uk-Youl;Kim, Hak-Il
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.517-519
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    • 2004
  • This paper describes an approach to estimate a robot pose with an image. The algorithm of pose estimation with an image can be broken down into three stages : extracting scale-invariant features, matching these features and calculating affine invariant. In the first step, the robot mounted mono camera captures environment image. Then feature extraction is executed in a captured image. These extracted features are recorded in a database. In the matching stage, a Random Sample Consensus(RANSAC) method is employed to match these features. After matching these features, the robot pose is estimated with positions of features by calculating affine invariant. This algorithm is implemented and demonstrated by Matlab program.

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Correspondence Estimation for Wide Area Watching Camera System (광역관찰 카메라 시스템을 위한 카메라의 대응관계 계산)

  • 이동휘;최승현;이칠우
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.415-418
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    • 2001
  • The automatic construction of large, high-resolution image mosaics is an active area of reasearch in the fields of photogrammetry, computer vision, image processing, and computer graphics. In this study, we describe a automatic mosaicing method that makes a panorama from images by placing camera in a emitted-grid. In the images captured by cameras, there must be a matched area and the area is in the particular area of the image. Initial transformation matrix, there(ore, is calculated from points searched in the partial area. It is possible to find best transformation matrix by Levenberg-Marquardt method. Finally, each images are multiplied by blending function and stitched by the transformation matrix to complete panoramic image.

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Spraying Status Evaluation of the Electro-static Sprayer Using Computer Image Processing (컴퓨터 영상처리를 이용한 정전분무기의 분무상태 평가)

  • Hwang, H.;Cho, S. I.;Cho, D. Y.
    • Journal of Biosystems Engineering
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    • v.24 no.5
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    • pp.391-398
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    • 1999
  • The spraying status of the electrostatic sprayer was evaluated by processing surface spraying images of the natural leaves. Water solution of the fluorescent material was used as a spray medium. The image of the lights reflected by fluorescent droplets was captured under UV light using a color CCD camera. Coverage rate, particle density, and the size distribution of particles were analyzed from the surface images of leaves under various spraying conditions such as spraying nozzle angle and object distance. Spraying characteristics of the electrostatic sprayer was evaluated in comparison with the conventional one. In a case of electrostatic sprayer, coverage rate and particle density increased by the average of 1.57times and 1.01times respectively under various nozzle angles and distances. The number of particle under the diameter of 50 ${\mu}{\textrm}{m}$ also increased significantly.

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A Study on the Automatic Measurement at an Unmanned Measuring Station Using Image Processing and Wireless Networks (화상처리 및 무선네트워크를 이용한 무인 측정 지점에서의 원격 계측 자동화에 관한 연구)

  • Lee, Han-Jun;Cha, Myung-Suk;Lee, Choong-Hoon
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.3
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    • pp.15-22
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    • 2007
  • An automatic measurement system which collects experimental data at an unmanned station where the networking to the internet could not be accessed was developed. With a Robo-rail accessing to the unmanned station, wireless local networking between server PC at the Rob-rail and client PC at the unmanned station is possible within 30 m from an access point equipment located at the unmanned station. An algorithm for transferring the data file which is saved in the client PC at the unmanned station to the server PC in the Robo-rail was proposed. IEEE-1394 camera was used to collect the data at the client PC. An extracting program from the IEEE-1394 captured images to character data and number data was developed using image processing technique, which drastically reduces the size of data file comparing to that of the raw image file.

Development of Wireless License Plate Region Extraction Module Based on Raspberry Pi (라즈베리 파이를 이용한 무선 자동차번호판 영역 추출 모듈 개발)

  • Kim, Dong-Kyung;Woo, Chong-Ho
    • Journal of Korea Multimedia Society
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    • v.18 no.10
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    • pp.1172-1179
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    • 2015
  • A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

Recognition of Car Manufacturers using Faster R-CNN and Perspective Transformation

  • Ansari, Israfil;Lee, Yeunghak;Jeong, Yunju;Shim, Jaechang
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.888-896
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    • 2018
  • In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.