• Title/Summary/Keyword: Focus Measure

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On the Measurement of the Depth and Distance from the Defocused Imagesusing the Regularization Method (비초점화 영상에서 정칙화법을 이용한 깊이 및 거리 계측)

  • 차국찬;김종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.6
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    • pp.886-898
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    • 1995
  • One of the ways to measure the distance in the computer vision is to use the focus and defocus. There are two methods in this way. The first method is caculating the distance from the focused images in a point (MMDFP: the method measuring the distance to the focal plane). The second method is to measure the distance from the difference of the camera parameters, in other words, the apertures of the focal planes, of two images with having the different parameters (MMDCI: the method to measure the distance by comparing two images). The problem of the existing methods in MMDFP is to decide the thresholding vaue on detecting the most optimally focused object in the defocused image. In this case, it could be solved by comparing only the error energy in 3x3 window between two images. In MMDCI, the difficulty is the influence of the deflection effect. Therefor, to minimize its influence, we utilize two differently focused images instead of different aperture images in this paper. At the first, the amount of defocusing between two images is measured through the introduction of regularization and then the distance from the camera to the objects is caculated by the new equation measuring the distance. In the results of simulation, we see the fact to be able to measure the distance from two differently defocused images, and for our approach to be robuster than the method using the different aperture in the noisy image.

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An Automatic Focusing Method Using Establishment of Step Size from Optical Axis Interval (광학축 간격의 스텝크기 설정을 통한 오토포커싱 방법)

  • Kim, Gyung Bum;Moon, Soon Hwan
    • Journal of the Semiconductor & Display Technology
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    • v.14 no.1
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    • pp.7-11
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    • 2015
  • In this paper, an automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It is very difficult to determine focusing step size and moving direction in one camera autofocusing. The proposed method can improve speed and accuracy of focusing by using the optical axis interval of two cameras, which is automatically set up as focusing step size. Also, it can determine moving direction from focus value comparisons of two cameras, and then solve ambiguity of one camera focusing. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.

Elliptic coordinate of connection point for collision-free path planning based on linear parametric curve (타원 궤적 연결점을 이용한 일차매개곡선에 기반한 충돌회피 궤적 계획)

  • 남궁인
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1128-1131
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    • 1996
  • The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.

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Monitoring of Micro-Drill Wear by Using the Machine Vision System (머신비전 시스템을 이용한 마이크로드릴 마멸의 상태감시)

  • Choi Young-Jo;Chung Sung-Chong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.6 s.249
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    • pp.713-721
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    • 2006
  • Micro-drill wear deteriorates accuracy and productivity of the micro components. In order to improve productivity and qualify of micro components, it is required to investigate micro-drill wear exactly. In this study, a machine vision system is proposed to measure the wear of micro-drills using a precision servo stage. Calibration experiments are conducted to compensate for the machine vision system. In this paper, worn volume, area and length are defined as wear amounts. Micro-drill wear is reconstructed as the 3D topography and the quantized wear amount by using the shape from focus (SFF) method and wear parameters. Experiments have been conducted with HSS twist micro-drills and SM45C carbon steel workpieces. Validity of the proposed machine vision system is confirmed through experiments.

Implementation of Measuring System for the Auto Focusing (자동 초점 조절 검사 시스템 설계 및 구현)

  • Lee, Young Kyo;Kim, Young Po
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.4
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    • pp.159-165
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    • 2012
  • The accurate focusing position should be determined for accurate measurements In VMS. Camera lens focusing is an important problem in computer vision and video measuring systems (VMS) that use CCD cameras and high precision XYZ stages. Camera focusing is a very important step in high precision measurement systems that use computer vision technique. The auto focusing process consists of two steps, the focus value measurement step and the exact focusing position determination step. It is suitable for eliminating high frequency noises with lower processing time and without blurring. An automatic focusing technique is applied to measure a crater with a one-dimensional search algorithm for finding the best focus. Throughout this paper, the suggested algorithm for the Auto focusing was combined with the learning. As a result, it is expected that such a combination would be expanded into the system of recognizing voices in a noisy environment.

Error Analysis of the Image Measurement System (영상 측정 시스템의 오차 분석)

  • 김준희;유은이;사승윤;김광래;유봉환
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.490-495
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    • 1996
  • Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To calibrate and generalize distortion phenomenon is important. Thus, we must fix the discrimination criteria which is collected by image recognition of precise focus. Also, radial distortion causes an inward or outward displacement of a given image point from its ideal location. This type of distortion is mainly caused by flawed radial curvature curve of the elements. Thus, we were analyzed the distortion in terms of the changed with lens magnification.

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한.미 FTA가 유가공품 시장에 미치는 영향 분석: 치즈 및 버터 시장을 중심으로

  • Kim, Seong-Hun;Jang, Do-Hwan
    • Food Industry
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    • s.206
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    • pp.26-41
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    • 2008
  • Recently, Korea have experienced numbers of FTAs with other countries, including Chile, EFTA(European Free Trade Association), Singapore, ASEAN(Association of South-East Asian Nations), and U.S. In particular, FTA with U.S. are expected to cause huge impact on food markets as well as agricultural sector in Korea. Many researches have analyzed and discussed about the impact on agricultural sector after Korean-U.S. FTA, but very small number of studies focus on the impact of Korean-U.S. FTA on food markets. The purpose of the paper is to discuss the impact of Korea-U.S. FTA on Korean dairy market. For the numerical simulations, this paper focus on the impact on cheese and butter markets. The results of numerical analysis in the paper will be helpful for the future research, because few (maybe no) studies conduct the numerical analysis to measure the impact of Korea-U.S. FTA on Korean food market.

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Measures on Improving Korean Language Skills by Using Shadowing Techniques (섀도잉(shadowing)기법을 활용한 한국어 수업 방안)

  • Hyun, Nam Ji
    • Journal of Korean language education
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    • v.29 no.2
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    • pp.49-72
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    • 2018
  • The purpose of this study is to introduce an efficient measure in Korean language education for learners of Korean by applying shadowing techniques which focus on improving not only listening and speaking skills but also reading and writing skills. First of all, the study discusses about the definition of shadowing along with the effect of shadowing. The second part will be about examining the proposed method related to shadowing technique which is comprised of original shadowing techniques and other techniques transformed from the original. Thirdly, the paper will be discussing background information of the shadowing technique in previous researches and experiments using shadowing techniques in Korean language education. Finally, there will be an introduction of learning measures that apply to skill unification. Most of the previous researches of the shadowing technique were limited to a few students with only mid-to-high level learners while this method could cover up to a wide range of learners. The most effective way of learning a foreign language would firstly be the suggested method and the focus should be on repetition and practice of the learners.

The Needs Analysis of Software Safety Education Program for Common Competency Area

  • Kang, Ji-Woon;Do, Sung-Ryong
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.960-971
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    • 2021
  • As the era of the 4th Industrial Revolution enters, the importance of software safety is increasing, but related systematic educational curriculum and trained professional engineers are insufficient. The purpose of this research is to propose the high priority elements for the software safety education program through needs analysis. For this purpose, 74 candidate elements of software safety education program were derived through contents analysis of literature and nominal group technique (NGT) process with five software safety professionals from various industries in South Korea. Targeting potential education participants including industrial workers and students, an on-line survey was conducted to measure the current and required level of each element. Using descriptive statistics, t-test, Borich needs assessment and Locus for focus model, 16 high priority elements were derived for software safety education program. Based on the results, suggestions were made to develop a more effective education program for software safety education.

A Through-focus Scanning Optical Microscopy Dimensional Measurement Method based on a Deep-learning Regression Model (딥 러닝 회귀 모델 기반의 TSOM 계측)

  • Jeong, Jun Hee;Cho, Joong Hwee
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.1
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    • pp.108-113
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    • 2022
  • The deep-learning-based measurement method with the through-focus scanning optical microscopy (TSOM) estimated the size of the object using the classification. However, the measurement performance of the method depends on the number of subdivided classes, and it is practically difficult to prepare data at regular intervals for training each class. We propose an approach to measure the size of an object in the TSOM image using the deep-learning regression model instead of using classification. We attempted our proposed method to estimate the top critical dimension (TCD) of through silicon via (TSV) holes with 2461 TSOM images and the results were compared with the existing method. As a result of our experiment, the average measurement error of our method was within 30 nm (1σ) which is 1/13.5 of the sampling distance of the applied microscope. Measurement errors decreased by 31% compared to the classification result. This result proves that the proposed method is more effective and practical than the classification method.