• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.568-571
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• 2005

This paper introduces a correlation-based surface matching algorithm that can be used to reconstruct the surface topography of an object that is scanned from multiple overlapping regions by an AFM. The image matching technique is applied to two neighboring images intentionally overlapped with each other. To account for the inaccuracy of the coarse stage implemented in AFM, all the six axes including the rotational degrees of freedom are successively matched to maximize the correlation coefficient. The results show that the proposed 6-axes image matching method is useful for expanding the measurement range of AFM.

• 소성∙가공
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• 제16권4호
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• pp.323-328
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• 2007

The residual stress in axial direction of the steel wires has been measured by using a method based on the combination of the focused ion beam(FIB) milling and digital image correlation(DIC) program. The residual stress is calculated from the measured displacement field before and after the introduction of a slot along the steel wires. The displacement is obtained by the digital correlation analysis of high-resolution scanning electron micrographs, while the slot is introduced by FIB milling with low energy beam. The experimental procedures are described and the feasibilities are demonstrated in steel wires fabricated with different conditions. It reveals that the tensile residual stress is formed in all steel wires and this is strongly influenced by the fabrication conditions.

• 대한임베디드공학회논문지
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• 제16권6호
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• pp.277-283
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• 2021

This paper addresses the problem of vision-based mask filter inspection for mask production systems. Machine learning-based approaches can be considered to solve the problem, but they may not be applicable to mask filter inspection if normal and anomaly mask filter data are not sufficient. In such cases, handcrafted image processing methods have to be considered to solve the problem. In this paper, we propose a hierarchical correlation-based approach that combines handcrafted image processing methods to detect anomaly mask filters. The proposed approach combines image rotation, cropping and resizing, edge detection of mask filter parts, average blurring, and correlation-based decision. The proposed approach was tested and analyzed with real mask filters. The results showed that the proposed approach was able to successfully detect anomalies in mask filters.

• 간호행정학회지
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• 제10권3호
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• pp.325-334
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• 2004

Purpose: The purpose of this study was to identify the image of nurses and the professional self-concept perceived by nursing students. Method: The subjects included were 93 students. The research tool was the Professional Self-Concept of Nurses Instrument(PSCNI) by Arthur and Image of Nurses by Yang. Result: 1. The professional self-concept consisted of 4 factors : flexibility, satisfaction, competence, empathy. 2. The image of nurse consisted of 4 factors : official image, maternal image, professional image. unfavorable image. 3. The average item score of PSCNI was $2.94{\pm}30$. 4. The average item score of nurse' image was $3.63{\pm}46$ 5. The Professional self-concept of nurses(p=.0001) and image of nurses(p=.001) was found to significantly according to satisfaction for major. 6. The correlation between professional self-concept and image of nurses revealed correlation of r=.315(p=.004). Conclusion: There was a association between professional self concept of nurses, image of nurses and satisfaction for major. Therefore it is required to develop education program and strategy that helps establish satisfaction for major so that nursing students can experience firm professional self concept and positive image of nursing.

• 대한통합의학회지
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• 제8권2호
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• pp.149-157
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• 2020

Purpose : The purpose of this study was that For high school students in Busan, in order to provide basic data in selecting dental hygienists by establishing the correct perception and image of dental hygienists by identifying the image of dentists and career doctors who will choose dental hygienists. Methods : The comparison of group differences with dental hygienists' images was analyzed with independent sample t-test and one-way ANOVA. Correlation between image factors of dental hygienists was analyzed using Pearson's correction coefficient. Results : The image for dental hygienists averaged 3.87 points overall, while the average for each area of the image was 4.09 points for professional images, 4.07 points for business images, 4.08 points for personal images and 3.28 points for social images. When choosing a career path, 18.8 percent said they would not consider dental hygiene, and if they said they would consider dental hygiene, both work, professional, personal and social images were significantly high (p<.05). Professional and professional images (r=.975, p<.05) in the correlation between factors of dental hygienist images, personal and professional images (r=.942, p<.05), social and professional images (r=.865, p<.05), business and personal images (r=.924, p<.05), business image and social image (r=.858, p<.05), personal and social images (r=.882, p<.05) expressed a statistically significant amount of correlation. Conclusion : The study found that high school students' image of dental hygienists was rather positive, but their social image was rather low, and most students did not consider dental hygiene. Therefore, specific measures will be needed to build a desirable image for dental hygienists and positively recognize dental hygienists with active promotion and career experience for dental hygienists in the future.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.553-558
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• 2002

Physical sensor model in pushbroom satellite images can be made from sensor modeling by rotation parameters and attitude parameters on the satellite track. These parameters are determined by the information obtained from GPS, INS, or star tracker. Provided from satellite image, an auxiliary data error is connected directly with an error of rotation parameters and attitude parameters. This paper analyzed how obtaining satellite images influenced errors of rotation parameters and attitude parameters. furthermore, for detailed analysis, this paper generated simulated satellite image, which was changed variously by rotation parameters and attitude parameters of satellite sensor model. Simulated satellite image is generated by using high-resolution digital aerial image and DEM (Digital Elevation Model) data. Moreover, this paper determined correlation of rotation parameter and attitude parameters through error analysis of simulated satellite image that was generated by various rotation parameters and attitude parameters.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1711-1714
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• 2003

The noise in an image degrades image quality and deteriorates coding efficiency of compression. Recently, various edge-preserving noise filtering methods based on the nonstationary image model have been proposed to overcome this problem. In most conventional nonstationary image models, however, pixels are assumed to be uncorrelated to each other In order not to increase the computational burden too much. As a result, some detailed information is lost in the filtered results. In this paper, we propose a computationally feasible adaptive noise smoothing algorithm which considers the nonstationary correlation characteristics of images. We assume that an image has a nonstationary mean and can be segmented into subimages which have individually different stationary correlations. Taking advantage of the special structure of the covariance matrix that results from the proposed image model, we derive a computationally efficient FFT-based adaptive linear minimum mean square error filter. The justification for the proposed image model is presented and the effectiveness of the proposed algorithm is demonstrated experimentally.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• 정보처리학회논문지B
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• 제10B권1호
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• pp.73-80
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• 2003

본 논문에서는 기준영상과 탐색영상 사이의 대응되는 특징 점을 정합 하는 알고리즘을 제안한다. 두 영상에서 특징 점을 찾기 위하여 Harris의 코너 점 검출기를 사용하였다. 기준영상의 각 특징 점에 대해, 정규상관계수가 임계치 이상인 탐색영상의 특징 점들로 후보 정합 점을 구한다. 최종적으로 동적 프로그래밍을 사용하여 후보 정합 점들 중에서 대응되는 특징 점을 구한다. 실험으로 인위적인 영상과 실제 영상에서 특징 점을 정합 하는 결과를 보였다.

• Computers and Concrete
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• 제33권5호
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• pp.481-496
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• 2024

Internal erosion around pipes can lead to the failure of earth dams through various mechanisms. This study investigates the displacement patterns in earth dam models under three different failure modes due to internal erosion, using digital image correlation (DIC) methods. Three failure modes—erosion along a pipe (FM1), pipe leakage leading to soil erosion (FM2), and erosion in a pipe due to defects (FM3)—are analyzed using two- and three-dimensional image- processing techniques. The internal displacement of the cross-sectional area and the surface displacement of the downstream slope in the dam models are monitored using an image acquisition system. Physical model tests reveal that FM1 exhibits significant displacement on the upper surface of the downstream slope, FM2 shows focused displacement around the pipe defect, and FM3 demonstrates increased displacement on the upstream slope. The variations in internal and surface displacements with time depend on the segmented area and failure mode. Analyzing the relationships between internal and surface displacements using Pearson correlation coefficients reveals various displacement patterns for the segmented areas and failure modes. Therefore, the image-based characterization methods presented in this study may be useful for analyzing the displacement distribution and behavior of earth dams around pipes, and further, for understanding and predicting their failure mechanisms.