• Title/Summary/Keyword: Directional Magnification

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A New Profilometry System for Precision Measurement of 3D Shape Using the Directional Magnification Control of a Laser Light Stripe (선모양을 한 레이저빔의 방향성 배율 확대를 이용한 정밀 형상측정 시스템)

  • Park, Seung-Kyu;Baik, Sung-Hoon;KIM, Cheol-Jung
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.5
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    • pp.60-65
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    • 1997
  • This paper proposes a profilometry system for precise surface contouring of 3D objects using a direc- tionally magnified image of a laser light stripe. The resolution of this system can be improved several times comparad with that of conventional systems without loss of spatial resolution and depth of measurement. A pair of cylindrical lens(a convex lens and a concave lens) are used for a directionally magnified image of a laser light stripe maintaining the same focal plane. Also, image processing procedures for image reconstruc- tions are described.

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Image Magnification Using Median Filter and Spatial Variation (메디안 필터와 공간 변화량을 이용한 영상 확대)

  • Kwak, Nae-Joung
    • The Journal of the Korea Contents Association
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    • v.7 no.9
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    • pp.72-80
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    • 2007
  • Image magnification is the estimation of a few pixel in images with high quality from a pixel of an image with low resolution and there have been studied many techniques to make images with high quality. In this paper, we propose an image interpolation method using median filter and spatial information. The proposed method makes an interpolating pixel using an average value of a median filtered value and an average value of two pixels correlated with an interpolating pixel tightly. Also we make the magnified image with improved quality to add the directional information of surrounding pixels and the characteristic of ones using average value and max value of spatial variation. We evaluate the performance using PSNR in the quality of enlarged image comparing the proposed method with existing methods. The results show the proposed method improves PSNR than the existing methods and make images preserving the characteristic of original imges.

Evaluation of ASCE 61-14 NSPs for the estimation of seismic demands in marginal wharves

  • Smith-Pardo, J. Paul.;Reyes, Juan C.;Sandoval, Juan D.;Hassan, Wael M.
    • Structural Engineering and Mechanics
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    • v.69 no.1
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    • pp.95-104
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    • 2019
  • The Standard ASCE 61-14 proposes the Substitute Structure Method (SSM) as a Nonlinear Static Procedure (NSP) to estimate nonlinear displacement demands at the center of mass of piers or wharves under seismic actions. To account for bidirectional earthquake excitation according to the Standard, results from independent pushover analyses in each orthogonal direction should be combined using either a 100/30 directional approach or a procedure referred to as the Dynamic Magnification Factor, DMF. The main purpose of this paper is to present an evaluation of these NSPs in relation to four wharf model structures on soil conditions ranging from soft to medium dense clay. Results from nonlinear static analyses were compared against benchmark values of relevant Engineering Design Parameters, EDPs. The latter are defined as the geometric mean demands that are obtained from nonlinear dynamic analyses using a set of 30 two-component ground motion records. It was found that SSM provides close estimates of the benchmark displacement demands at the center of mass of the wharf structures. Furthermore, for the most critical pile connection at a landside corner of the wharf the 100/30 and DMF approaches produced displacement, curvature, and force demands that were reasonably comparable to corresponding benchmark values.

AN IN-VITRO EVALUATION OF SEALER PLACEMENT METHODS IN SIMULATED ROOT CANAL EXTENSIONS (근관 내 불규칙 확장부에서 sealer 적용방법에 따른 충전 효과 평가)

  • Kim, Sung-Young;Lee, Mi-Jeong;Moon, Jang-Won;Lee, Se-Joon;Yu, Mi-Kyung
    • Restorative Dentistry and Endodontics
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    • v.30 no.1
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    • pp.31-37
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    • 2005
  • The aim of this study was to evaluate the effectiveness of sealer placement in simulated root canal extensions. Forty resin blocks were attained from the Endo-training Bloc. In each block. The simulated root canal was made with $\#20$, 80taper GT file. After each block was longitudinally split into two halves, a standardized groove was prepared on one canal wall of two halves to simulate the canal extensions with various irregularities. The two halves of each block were assembled and all simulated root canals were obturated by single cone method with AH26 sealer. Four different methods of sealer placement were used: group A, $\#20$ K-file; group B, ultrasonic file; group C, lentulo spiral; group D, EZ-Fill bi-directional spiral. All obturated blocks were stored in $100\%$ humidity at $37^{\circ}C$ for 1 week, Using a low speed saw, each block was sectioned horizontally. Images of the sections were taken using a stereomicroscope at $\times$ 30 magnification and a digital camera. The amount of the sealer in the groove was evaluated using a scoring system, a higher score indicated better sealing effectiveness. The data was statistically analysed by Fisher's Exact Test. The sealing score was the lowest, specially at the middle area of canal extensions in group A, and that was statistically significant difference from other groups. In conclusion, the ultrasonic file, lentulo spiral and EZ-Fill bi-directional spiral were effective methods of sealer placement in simulated canal extensions. The K file was the least effective method, specially at the middle area of canal extensions.

Nucleus Recognition of Uterine Cervical Pap-Smears using Fuzzy Reasoning Rule (퍼지 추론 규칙을 이용한 자궁 경부진 핵 인식)

  • Kim, Kwang-Baek;Song, Doo-Heon
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.3
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    • pp.179-187
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    • 2008
  • In this paper, we apply a set of algorithms to classily normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining $1{\times}400$ microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.

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