• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.238-244
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• 2021

Image mosaicking is a common and useful technique to visualize a global map by stitching a large number of local images obtained from visual surveys in underwater environments. In particular, visual inspection of underwater structures using underwater robots can be a potential application for image mosaicking. Feature-based pairwise image registration is a commonly employed process in most image mosaicking algorithms to estimate visual odometry information between compared images. However, visual features are not always uniformly distributed on the surface of underwater structures, and thus the performance of image registration can vary significantly, which results in unnecessary computations in image matching for poor-conditioned image pairs. This study proposes a pairwise registrability measure to select informative image pairs and to improve the overall computational efficiency of underwater image mosaicking algorithms. The validity and effectiveness of the image mosaicking algorithm considering the pairwise registrability are demonstrated using an experimental dataset obtained with a full-scale ship in a real sea environment.

• Journal of Korean Academy of Nursing
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• v.32 no.6
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• pp.906-916
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• 2002

The purpose of this study was to identify the change and difference and relationship of postpartum depression and physical image. Method: The subjects consisted of 86 postpartum women at one general hospital in Seoul. The data was collected from September to November 2001. The instrument used for this study were SRD (Self-Rating Depression Scale) and Norris' Body Image Scale to evaluate depression and body image. The collected data was analyzed with frequency, mean, t-test, paired t-test, ANOVA and Pearson's correlation coefficient. Result: The result of this study were as follows: 1. The mean score of D2 was significantly higher than D1(p=.003). There was no difference significantly B1 and B2(p=310). 2. There was significant correlation between the two, D1-D2(r=.381, p<.01), B1-B2(r=.364, p<.01), D1-B1(r=.579, p<.01), D2-B2(r= .567, p<.01). (*D1: depression of postpartum 1-3days, D2: depression of postpartum 6-8weeks, B1: body image of postpartum 1-3days, B2: body image of postpartum 6-8weeks) Conclusion: There was very high postpartum depression in postpartum women, but body image was positive. Also, there was correlated to postpartum depression and body image. Thus it is necessary to implement nursing intervention focused on to decrease the postpartum depression and to enhance the body image of the postpartum women.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.593-601
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• 2016

This paper is related to the Region-based Spectral Correlation Estimation(RSCE) coding method that makes it possible to achieve the high-compression ratio by estimating color component images from luminance image. The proposed method is composed of three steps. First, Y/C bit-plane summation image is defined using normalized chrominance summation image and luminance image, and then the Y/C bit-plane summation image is segmented for extracting the shape information of the regions. Secondly, the scale factor and the offset factor minimizing the approximation square errors between luminance image and R, B images by the each region are calculated. Finally, the scale factor and the offset factor for the each region are encoded into bit stream. Referring to the results of computer simulation, the proposed method provides more than two or three times higher compression ratio than JPEG/Baseline or JPEG2000/EBCOT algorithm in terms of bpp needed for encoding two color component images with the same PSNR.

• Korean Journal of Health Education and Promotion
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• v.6 no.1
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• pp.91-105
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• 1989

The purpose of this study is to identify the body images of patints with low back pain and their status on adjustment of daily living. The data were collected from 11 general hospitals during Feburary 2, 1987 through May 30,1987. One hundred and ninety five subjects having physical therapy treatment because of low back pain were analyzed. For measurement of body image, 11 pairs of adjectives were used on semantic differential scale, and for measurement of adjustment of daily living, 10 items were used on a likert type scale. Results of the study are summerised as follows. 1. The average patient age were 34yeats and 62% of the patients were men. High school grade completed were 43.1% and Cause of Low Back Pain were respctively;Unknown etiology 31.8%, lifting heavy objects 27.7%, Traffic accident and injury 17.9%. Types of treatment were;medication plus physical therapy 54.9%, physical therapy only 22.6%. Average treatment duration were 24.5 months. 2. There were significant difference in the body image between before low back pain and after low back pain. The body image before low back pain were 59.89(Mean) but after low back pain were 37,24(Mean) and two groups were statistically significant (t=21.3, p<0.00l). 3. there were no significant difference in the body image between the male and female.(t=1.49, p＞0.05) 4. The correlation between body image and adjustment of daily living. in both sexes showed positive correlation coefficient; male(r=0.4648, p<0.00l) female(r=0.4516, p<0.00l) respectively. It means that patients with positive body image can adjust well in daily living. 5. The relation between the body image and general variables revealed sigificant difference with occupation and age.(F=2.12 p<0.05, F=3.48 p<0.05). That is different occupation and different age groups can show different body image. In conculsion with the above results, It is my strong belief that multidisciplinary approach including the concept of body image and patient education about postural care, activities of daily living, lifting mechanics should be applied in treating and dealing with those patients.

• Journal of Radiation Protection and Research
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• v.35 no.1
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• pp.26-33
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• 2010

A computed Radiography (CR) system by use of reusable Image Plate (IP) offers a convenient and reliable way to replace a conventional film-screen system for NDT (non-destructive testing) field. The quality of a radiography to detect a defect of welded objects depends on the procedure embracing several factors such as measurement conditions, image plate type/class, radiation energy, radiation type, and source to image plate distance. Also, the ability of images to detect a flaw reduces with increasing object thickness. In the study, the properties of gamma ray source were summarized for NDT field and inspection images of CR image system manufactured by FUJI were acquired using $^{75}Se$ and $^{192}Ir$ with welded objects. We analyzed the gray scale of hole defect image by using XCAP image processing program and calculated the image contrast and SNR in definition. Also the sesitivities of image quality indicator(IQI) were calculated for hot and cooling tube image of $^{75}Se$ and $^{192}Ir$.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.47-55
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• 2002

Remote sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation./sup 1)/ EOC (Electro -Optical Camera) sensor loaded on the KOMPSAT-1 (Korea Multi- Purpose Satellite-1) performs the earth remote sensing operation. EOC can get high-resolution images of ground distance 6.6m during photographing; it is possible to get a tilt image by tilting satellite body up to 45 degrees at maximum. Accordingly, the device developed in this study enables to obtain images by photographing one pair of tilt image for the same point from two different planes. KOMPSAT-1 aims to obtain a Korean map with a scale of 1:25,000 with high resolution. The KOMPSAT-1 developed automated feature extraction system based on stereo satellite image. It overcomes the limitations of sensor and difficulties associated with preprocessing quite effectively. In case of using 6, 7 and 9 ground control points, which are evenly spread in image, with 95% of reliability for horizontal and vertical position, 3-dimensional positioning was available with accuracy of 6.0752m and 9.8274m. Therefore, less than l0m of design accuracy in KOMPSAT-1 was achieved. Also the ground position error of ortho-image, with reliability of 95%, is 17.568m. And elevation error showing 36.82m was enhanced. The reason why elevation accuracy was not good compared with the positioning accuracy used stereo image was analyzed as a problem of image matching system. Ortho-image system is advantageous if accurate altitude and production of digital elevation model are desired. The Korean map drawn on a scale of 1: 25,000 by using the new technique of KOMPSAT-1 EOC image adopted in the present study produces accurate result compared to existing mapping techniques involving high costs with less efficiency.

• Korean Institute of Interior Design Journal
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• no.16
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• pp.3-9
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• 1998

The purpose of this research is to empirically validate the IIPS (Interior Image Preference Scale) which is a newly developed visual instrument for evaluating the environmental disposition inherent to individuals especially one's interior image preferences. The questionnaire survey was used. The data were collected from Oct. 10th 1997 to Nov. 14th 1997. The subjects were 399 undergraduate students and 30 professor of Dep. of Interior Design. With respect to content validity and construct validity of IIPS discrimination and similarity structure of scales and characteristics of 12 prototype interior images were examined in comparison with the originals. 429 questionnaires were analyzed using frequency percentage mean and Multi-Dimensional Scales. The major results were as follows (1) All 80 items of IIPS were discriminated by 3 criteria such as Traditionalism·Modernity(TM) Masculinity·Femininty (MF) and Simplicity·Complexity (SC) as expected at the time of the instrument development stage.(2) 12 prototype interior images of the IIPS showed tendency to be accord with descriptors to express them in comparison with the originals (3) All 90 items of IIPS showed a cluster distribution according to the similarity structure of scales. Three subscales of IIPS(e . g. TM MF and SC) were structured pretty well by those 3 dimensions. This research revealed the IIPS to have content validity and construct validity for evaluating of preference of three properties of interior image in empirical research. The IIPS was found to be potential objective tool to measure the interior image preferences.

• Journal of Korean Society of Rural Planning
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• v.16 no.3
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• pp.1-10
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• 2010

The purpose of this study is to find out the color preference on rural rooftop color. Today, public profit value of a rural community has been heavily recognized in the areas of preservation of pro-environmental and traditional life styles and foundation of collective community. Comparatively with urban, rural town conserves the scenic of those days when the historic landscape existed. Therefore, elements of historic and tradition in rural town are interesting resources to people who want traditional experience. Color is one of the most influenced elements for the image of Landscape. On the other hand, radical modernization has brought conflicting color element that does not blend with existing environmental color. Among others, roof represents one of the important traits of rapidly developing rural community due to vast amount of space it covers. In order to come up with more appropriate coloring scheme, it is necessary determine color that forms a balance with present conditions of rural life and historic landscape. This study provides more objective rooftop coloring selection process by employing additional surveys regarding color image adjective. I justified necessity of the balance between environmental color and roof color through analyzing correlation between environmental color of the rural town and Color Image Scale of the preliminary selection of roofs.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.201-209
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• 2011

This paper suggests a panorama image stitching system which consists of an image matching algorithm: modified SURF (Speeded Up Robust Feature) and an image blending algorithm: multi-band blending. In this paper, first, Modified SURF is described and SURF is compared with SIFT (Scale Invariant Feature Transform), which also gives the reason why modified SURF is chosen instead of SIFT. Then, multi-band blending is described, Lastly, the structure of a panorama image stitching system is suggested and evaluated by experiments, which includes stitching quality test and time cost experiment. According to the experiments, the proposed system can make the stitching seam invisible and get a perfect panorama for large image data, In addition, it is faster than the sift based stitching system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.454-475
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• 2018

This paper presents a novel Android malware classification model planned to classify and categorize Android malicious code at Drebin dataset. The amount of malicious mobile application targeting Android based smartphones has increased rapidly. In this paper, Restricted Boltzmann Machine and Deep Belief Network are used to classify malware into families of Android application. A texture-fingerprint based approach is proposed to extract or detect the feature of malware content. A malware has a unique "image texture" in feature spatial relations. The method uses information on texture image extracted from malicious or benign code, which are mapped to uncompressed gray-scale according to the texture image-based approach. By studying and extracting the implicit features of the API call from a large number of training samples, we get the original dynamic activity features sets. In order to improve the accuracy of classification algorithm on the features selection, on the basis of which, it combines the implicit features of the texture image and API call in malicious code, to train Restricted Boltzmann Machine and Back Propagation. In an evaluation with different malware and benign samples, the experimental results suggest that the usability of this method---using Deep Belief Network to classify Android malware by their texture images and API calls, it detects more than 94% of the malware with few false alarms. Which is higher than shallow machine learning algorithm clearly.