• 가정간호학회지
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• 제24권3호
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• pp.336-344
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• 2017

Purpose: The purpose of this study was to examine job recognition of female nurses and perceived image of male nurses, and to investigate predictive factors affecting this perceived image. Methods: A survey was conducted between September and October 2015 with 143 female clinical nurses who worked at hospitals. Data were analyzed using the SPSS 21.0 correlation and multiple regression analyses. Results: The findings of this study were as follows : Female nurses recognition had positive correlations with images of male nurses. Social image(r=.41, p<.001), professional image(r=.45, p<.001), and nursing job prospects(r=.49, p<.001) were significantly correlated with perceived image of male nurses. Nursing job prospect(${\beta}=.193$, p=.049), perception that male nurses were suitable for their jobs(${\beta}=.329$, p<.001), mass media experience related to male nurses(${\beta}=.244$, p<.001), social image(${\beta}=.225$, p=.009) and professional image(${\beta}=.191$, p=.021) explained 42.7% of the variance in image of male nurses. Conclusions: The findings of this study suggest that nursing education and research should find concrete ways to improve perceived image of male nurses. It will enhance the quality of nursing service by improving male nurses' communication and collaboration with female nurses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.6177-6200
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• 2018

In order to achieve the goal of protecting medical images, some existing watermark techniques for medical image protection mainly focus on improving the invisibility and robustness properties of the method, in order to prevent unnecessary medical disputes. This paper proposes a novel copyright method for medical image protection based on visual secret sharing (VSS) and cellular automata transform (CAT). This method uses the protected medical image feature as well as VSS and a watermark to produce the ownership share image (OSI). The OSI is used for medical image verification and must be registered to a certified authority. In the watermark extraction process, the suspected medical image is used to generate a master share image (MSI). The watermark can be extracted by combining the MSI and the OSI. Different from other traditional methods, the proposed method does not need to modify the medical image in order to protect the copyright of the image. Moreover, the registered OSI used to verify the ownership and its appearance display meaningful information, facilitating image management. Finally, the results of the final experiment can prove the effectiveness of our method.

• 전기전자학회논문지
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• 제27권3호
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• pp.280-287
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• 2023

딥러닝의 발전은 컴퓨터 비전 문제를 해결할 수 있지만, 높은 정확도를 위해서는 대규모 데이터셋이 필요하다. 본 논문에서는 객체 바운딩 박스와 이미지 엣지 성분을 이용한 이미지 생성 기법을 제안한다. 객체 탐지를 통해 이미지 내의 객체 바운딩 박스를 추출하고 이미지 엣지 성분을 함께 이미지 생성모델의 입력값으로 사용하여 새로운 이미지 데이터를 생성한다. 실험 결과, 제안 기법으로 생성된 이미지는 이미지 품질 평가에서 소스 이미지와 유사한 품질을 보였고, 딥러닝 훈련과정에서도 좋은 성능을 보였다.

• 한국생활과학회:학술대회논문집
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• 한국생활과학회 2010년도 하계학술대회
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• pp.149-151
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• 2010

• Journal of Ecology and Environment
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• 제41권4호
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• 한국멀티미디어학회논문지
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• 제19권4호
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• pp.725-735
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• 2016

High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.

• 디지털융복합연구
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• 제18권4호
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• pp.75-80
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• 2020

본 연구는 중국시장에서 미시 및 거시적 국가이미지가 브랜드태도에 영향을 미치는 영향관계에서 브랜드친숙도, 개방성의 조절효과를 검증하였다. 이를 위해 기존 문헌에 대한 고찰을 바탕으로 거시적 국가이미지의 하위 요인을 경제적 이미지로 사용하였다. 본 연구에서 사용된 연구 방법은 주로 선행 문헌 연구 방법과 실증 연구 방법을 포함하며, 선행연구 이론들을 바탕으로 연구 모형을 수립하고 관련 연구 가설을 설정하는 동시에 중국소비자를 설문 대상으로 선정하여 설문 조사 및 데이터 수집을 실시하고 모형의 적합성 테스트 및 연구 가설에 대해 검증하였다. 본 연구의 결과, 미시적 및 거시적 국가이미지는 브랜드 태도에 정(+)의 영향을 미치고 브랜드 친숙도와 개방성은 미시적 국가이미지에는 조절효과 없는 것으로 분석되었고 거시적 국가이미지(경제이미지)에는 조절효과가 있는 것으로 분석되었다. 본 연구의 결과는 중국시장에서 중국과 밀접한 관계를 맺고 있는 한국, 미국, 일본기업들의 다양한 비즈니스 전략을 활용하는데 시사점을 제공하고 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.204-207
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• 2002

The current paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm In the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3D-SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• 전자공학회논문지SC
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• 제37권1호
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• pp.49-55
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• 2000

흉부의 병변을 진단하기 위해 주로 사용되고 있는 흉부 X-선 촬영은 최근 컴퓨터 기술의 발달에 힘입어 디지털화 되고 있다. 디지털화된 흉부 영상을 방사선과 전문의가 모니터 상에서 관찰할 때 흉부 영상의 품질이 고르지 못하여 병변을 검출하기가 어려울 뿐만 아니라 이로 인하여 많은 진단 시간이 소요된다. 따라서 본 연구에서는 디지털 흉부 영상을 개선하기 위해 신경망을 이용하여 흉부 X-선 영상의 등화 방법을 제안하고 그 결과를 히스토그램 등화 방법과 비교하여 제시하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1990년도 추계학술대회
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• pp.42-47
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• 1990

In this paper, a new adaptive image processing method based on human visual system has been presented. The basic idea behind the proposed method is to improve the efficiency of the information transfer channel regionally by manipulating the displayed image in order to compensate the regional inefficiency of the information transfer channel. The proposed method consists of two parts; the first part reallocates pixel values corresponding to high X-ray attenuation to that of more intense X-ray exposure by multiplying the pixel values with the local adaptive multiplcation factor, and the second part adjusts the pixel values of dark area of displayed image such as overexposed lung area to be more bright. The processed image with the proposed method shows significantly increased visibility of mediastinal and subdiaphramatic area, and also the lung area of over exposed case without any artifact.