• 제목/요약/키워드: Image Processing Method

검색결과 4,578건 처리시간 0.03초

영상처리기법을 이용한 CCT 시편 균열의 자동관측법에 관한 연구 (The Measurement of the Crack in CCT Specimen Using the Image Processing Techniques)

  • 이현우;문기태;오세종;정병우
    • 대한기계학회논문집A
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    • 제21권3호
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    • pp.528-533
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    • 1997
  • In the analysis of fatigue crack propagation behavior, the crack length is one of the most important factors. In the test of crack propagation, compliance method is widely used to detect crack length. The measurement of surface crack length is not so easy with compliance method. In this study, the image processing technique was applied to measure the surface crack length. CCD(Charge-coupled device) camera was used to observe the crack image and the computer program to detect crack length from stored crack image was developed. CCT(Center Cracked Tension) specimen was used to compare the compliance method with the image processing technique. The crack length which detected by the image processing techniques was found to be well consistent with that from the optical measurement.

영상처리 기법을 이용한 주탑의 변위 측정 (Displacement Measurement of Pylon using Image Processing Technique)

  • 손병직;전승곤;허광희
    • 복합신소재구조학회 논문집
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    • 제6권3호
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    • pp.20-25
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    • 2015
  • This paper introduces a digital image processing(DIP) method as a method for measuring the displacement of pylon. The comparison of DIP results and ANSYS analysis results verified the validity of the image processing technique. Normalized cross-correlation(NCC) coefficient was used and experiments were performed three times. It shows that the displacement difference was 22% and 5% compared to ANSYS results. Therefore, the image processing method is expected to be able to measure the displacement of pylon sufficiently.

과실수확(果實收穫) 로봇에 관한 연구(硏究)(II) -폐쇄회로(閉鎖回路) TV 카메라에 의한 과실(果實)의 위치검출(位置檢出)- (Development of a Fruit Harvesting Robot(II) -Determination of Fruit Location by a Closed-Circuit TV Camera-)

  • 류관희;노상하;김영호
    • Journal of Biosystems Engineering
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    • 제14권2호
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    • pp.104-114
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    • 1989
  • The most important subject in developing agricultural robots for fruit harvesting is to detect accurately the location of a fruit about the given coordinate system. This study was carried out to develop an image processing algorithm which enables finding out the three dimensional locations of a fruit. The digital image processing device consisted of an optosensor (Closed-circuit TV camera), image processing interface board (Digitizer) and microcomputer (IBM PC/AT). A stereo-image processing method using the two cameras attached to the manipulator was evaluated through experiment with apples. The accuracy and quickness of detecting the location of apples by this method was not satisfactory. The maximum errors of the detected locations by the stereo-image processing method in x-, Y-, and z- directions were 3, 4 and 4 cm, respectively. The maximum time required to get the rectangular coordinate data of a fruit was about 2 minutes.

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기계의 상태 모니터링을 위한 최적의 마멸분 영상 획득 방법에 관한 연구 (A Study on the Optimum Image Capture of Wear Particle for Condition Monitoring of Machine)

  • 조연상;박흥식
    • Tribology and Lubricants
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    • 제23권6호
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    • pp.301-305
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    • 2007
  • The wear particle analysis has been known as very effective method to foreknow and decide a moving situation and a damage of machine parts by using the digital computer image processing. But it was not laid down and trusted to calculate shape parameters of wear particle and wear volume. In order to apply image processing method in the foreknowledge and decision of lubricated condition, it needs to verify the reliability of the calculated data by the image processing and to lay down the number of images and the amount of wear particle in one image. In this study, the lubricated friction experiment was carried out in order to establish the optimum image capture with the SM45C specimen under experiment condition. The wear particle data were calculated differently according to the number of image and the amount of wear particle in one image.

이미지 보간기법의 성능 개선을 위한 비국부평균 기반의 후처리 기법 (Non-Local Mean based Post Processing Scheme for Performance Enhancement of Image Interpolation Method)

  • 김동형
    • 디지털산업정보학회논문지
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    • 제16권3호
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    • pp.49-58
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    • 2020
  • Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

영상 처리 방법을 이용한 구조물의 저주파수 진동 계측 (Measurement of Low-Frequency Vibrations of Structures Using the Image Processing Method)

  • 김기영;곽문규
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 추계학술대회논문집
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    • pp.503-507
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    • 2004
  • This paper is concerned with the measurement of low-frequency vibrations of structures using the image processing method. To measure the vibrations visually, the measurement system consists of a camera, an image grabber board, and a computer. The specific target installed on the structure is used to calculate the vibration of structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the size of image. In this paper, we discuss the methodology for the vibration measurement using the image processing method. The method enables us to measure the displacement directly without any contact. The resolution of the vibration measurement can be refined but limited to the sub centimeter displacement.

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기계 시각과 인공 신경망을 이용한 파란의 판별 (Detection of Surface Cracks in Eggshell by Machine Vision and Artificial Neural Network)

  • 이수환;조한근;최완규
    • Journal of Biosystems Engineering
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    • 제25권5호
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    • pp.409-414
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    • 2000
  • A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.

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탄성 유체 윤활에서의 유막 두께 측정에 관한 정성적 분석 (Qualitative Analysis of Film Thickness in Elastohydrodynamic Lubrication)

  • 최언진;장시열
    • 한국윤활학회:학술대회논문집
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    • 한국윤활학회 1999년도 제29회 춘계학술대회
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    • pp.147-155
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    • 1999
  • The film thickness and shape of elastohydrodynamic lubrication is measured by optical interferometer, which is the most precise method for EHL film measurement. However the interpretation of the image pattern from optical viscometer is not easy for two-dimensional shape. A newly developed method of image processing makes it possible to evaluate the film thickness and shape in every point of contact region with two dimensional aspects. In this study, we captured film shape of EHL film from the monochromatic incident light with the Image processing method, which uses phase shift method, and obtained the image analysis method for gray level image in order to qualitatively evaluate film shapes.

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A fast high-resolution vibration measurement method based on vision technology for structures

  • Son, Ki-Sung;Jeon, Hyeong-Seop;Chae, Gyung-Sun;Park, Jae-Seok;Kim, Se-Oh
    • Nuclear Engineering and Technology
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    • 제53권1호
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    • pp.294-303
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    • 2021
  • Various types of sensors are used at industrial sites to measure vibration. With the increase in the diversity of vibration measurement methods, vibration monitoring methods using camera equipment have recently been introduced. However, owing to the physical limitations of the hardware, the measurement resolution is lower than that of conventional sensors, and real-time processing is difficult because of extensive image processing. As a result, most such methods in practice only monitor status trends. To address these disadvantages, a high-resolution vibration measurement method using image analysis of the edge region of the structure has been reported. While this method exhibits higher resolution than the existing vibration measurement technique using a camera, it requires significant amount of computation. In this study, a method is proposed for rapidly processing considerable amount of image data acquired from vision equipment, and measuring the vibration of structures with high resolution. The method is then verified through experiments. It was shown that the proposed method can fast measure vibrations of structures remotely.

이미지 기반의 식물 인식 기술 동향 (Trends of Plant Image Processing Technology)

  • 윤여찬;상종희;박수명
    • 전자통신동향분석
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    • 제33권4호
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    • pp.54-60
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    • 2018
  • In this paper, we analyze the trends of deep-learning based plant data processing technologies. In recent years, the deep-learning technology has been widely applied to various AI tasks, such as vision (image classification, image segmentation, and so on) and natural language processing because it shows a higher performance on such tasks. The deep-leaning method is also applied to plant data processing tasks and shows a significant performance. We analyze and show how the deep-learning method is applied to plant data processing tasks and related industries.