• Journal of Home Health Care Nursing
• /
• v.24 no.3
• /
• pp.336-344
• /
• 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)
• /
• v.12 no.12
• /
• pp.6177-6200
• /
• 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.

• Journal of IKEEE
• /
• v.27 no.3
• /
• pp.280-287
• /
• 2023

Deep learning advancements can solve computer vision problems, but large-scale datasets are necessary for high accuracy. In this paper, we propose an image generation technique using object bounding boxes and image edge components. The object bounding boxes are extracted from the images through object detection, and image edge components are used as input values for the image generation model to create new image data. As results of experiments, the images generated by the proposed method demonstrated similar image quality to the source images in the image quality assessment, and also exhibited good performance during the deep learning training process.

• 한국생활과학회:학술대회논문집
• /
• 2010.05a
• /
• pp.149-151
• /
• 2010

• Journal of Ecology and Environment
• /
• v.41 no.4
• /
• pp.114-119
• /
• 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.

• Journal of Korea Multimedia Society
• /
• v.19 no.4
• /
• pp.725-735
• /
• 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.

• Journal of Digital Convergence
• /
• v.18 no.4
• /
• pp.75-80
• /
• 2020

This study verified the moderating effect of brand familiarity and openness in the relationship between micro and macro-national image in Chinese market and brand attitude. The research methods used in this study based on previous studies, a research model was established, related research hypotheses were set up, and Chinese consumers were selected as survey subjects to conduct surveys and data collection, and the suitability test and research hypothesis of the model were verified. As a result of this study, Micro and macro-national image had a positive effect on brand attitude, brand familiarity and openness had no moderating effect on micro-national image, and macro-national image had a moderating effect on macro-economic image. The results of this study provide implications for companies in Korea, the United States, and Japan, which have close relations with China in the Chinese market, to utilize various business strategies.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.204-207
• /
• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.1
• /
• pp.49-55
• /
• 2000

Recently, X-ray chest rediography is showing a tendency to take an image of digital radiography so as to diagnose the pathology of chest in a usual. When the radiologist observes the chest image derived from digital radiography system on the monitor, he feels difficult to find out the pathological pattern because the quality of chest radiography is unequal. It takes amount of time to adjust the proper image for diagnosis. Therefore, we propose the method of the chest image equalization using neural networks and provide the compared result with histogram equalization method.

• Proceedings of the KOSOMBE Conference
• /
• v.1990 no.11
• /
• pp.42-47
• /
• 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.