• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.4
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• pp.81-89
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• 2007

Urban landscape represents a city's internal identity as well as external form. Therefore, urban landscape and image planning has to involve marketing strategies to deliver the economic growth and regional revitalization through recreating the environmental and cultural value of the city. This study intends to develop practical city image management programs as city marketing tools which consider opinions of local authorities, related experts, and residents. To achieve this purpose conjoint analysis was applied on three components which symbolically reflects features of assets and resources in Anseong. This study can be summarized as follows: 1. The first consideration for Lake Geumgwang is to develop farm experience Programs on waterside fields. 2. The rot consideration for Bauduki Festival is to make efforts for public relations(PR) to be able to merchandise festival-related goods and develop unique products. 3. The first consideration for Anseong Grapes is to build leisure-oriented theme parks for local farm products. This study is meaningful to develop the efficient and quantitative management method of city image for marketing. The integrated approach to the management programs to reflect opinions of local policies, experts and citizens is expected to become a useful foundation in studying city images and marketing.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.8
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• pp.1275-1287
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• 2006

This was to confirm the Web-SFAS and street Fashion trend 2005. Korea women's street fashion in 2005 S/S was analyzed by using the Web-SFAS(Street Fashion Analysis System) that was developed and completed in the earlier research. Total 270 women who were sensitive to the fashion were surveyed around in 5 nationwide cities and 9 commercial zones. The analysis results of the questionnaire and image survey in 2005 S/S for each commercial zone is shown as follows: 1. The sequence of care with most interest in producing fashionable shape is in the order of clothes>accessory>hair style>make up>shoes, and it was found that the proper reason for visiting the commercial zone is to meet with friends than shopping. 2. Most preferred item for tops were shirts and T-shirts, while for bottoms were blue jeans of denim material in various colors and designs. The color had the clear winner in white color with the pink or yellow line of colors preferred in all commercial zones. The blue jeans and skirt items were the most dominant with the preference on the blue color. The color and image were diversely favored with light, natural, modern, elegance and warm images. 3. The semi-formal image was preferred in women's street fashion, 2005 S/S in Apgujeong-dong, Hapseong-dong, Myeong-dong, Hongik University area, Dongseong-ro, and the active comfort casual image was preferred by womens in Seo-myeon, Nampo-dong and Sangnam-dong. However the retro image were represented in Daehak-ro specially. The tendency of street fashion for women had the difference of their own trends for each commercial zone, rather then the regional differences for each city with the conspicuous preference of color for the items.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.265-272
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• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.418-421
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• 2007

It is important to maintain information by application or 3D modeling through the satellite and UAV image which is a real world. The prevention business has recognized the need for accurate 3-D geospatial information around the disaster region to identify objects to 3D modeling. In this paper, we presented an approach to create 3D model and loading, processing the image using GIS techniques, and the digital topographic maps were used for the DEM and the features of the area. The result is a implementation of the simple application that illustrates the objects in 3-D. The presented approach will be used for identifying objects and assisting in regional planning around the airfields.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2006.11a
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• pp.213-214
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• 2006

Now days subway represents a gateway of the city and a center of transportation. It belongs basic facilities to connect the town and suburbs and has strongly regarded as a means of development of city. but It's time that the subway should be changed to reach the needs which give visitors comfortable space and convenient image to use it and it also has a function of transportation because the present generation have turned an information-oriented and specialized society. So we try to put the essential points as like the followings, designing the CANOPY (Busan subway-3rd line). the first, We create an distinctive image with effect to get a regional self-confidence the second, we make new traffic space including potential energy in new millennium ages the third, we need an effort and experiment to overcome contradiction pointing to unity between varieties. To conclude, we want to create CANOPY subway with an individual characters for Busan and aim at a fine view and improved image of subway for Busan, considering the belows.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.211-220
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• 2015

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

• Journal of the Korean Society for information Management
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• v.16 no.4
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• pp.95-107
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• 1999

Various approaches have been made for dividing images in content-based image retrieval. One of them defined five regions for images and conducted a series of experiments. A major assumption of the experiment is that the center regions of images are very important. It is based on the observation that meaningful objects are usually located in the center region of images. From this point of view, we tried to test if the assumptions is objectively valid by calculating and comparing PIM(Picture Information Measure) entropies of image regions proposed by S.K Chang. The experimental results showed that there were statistical PIM differences between the center and other regions.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1365-1372
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• 2011

This paper proposes a cognitive contrast enhancement algorithm based on the non-linear masking to advance low cognitive contrast in dark regions of images. In order to improve brightness in dark regions of an image, we propose a new contrast enhancement algorithm based on the non-linear masking using regional adaptive parameters of an image. For performance evaluation of the proposed method, chromaticity and saturation comparison as a quantitative assessment and z-score comparison as a qualitative assessment were executed between test images and their simulated images by SSR, MSR, a conventional non-linear masking and the proposed method, respectively. As a result, the proposed method showed low chromaticity and saturation difference and improved cognitive contrast for the three methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.502-504
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• 1995

In video image compression, it is important to extract the exact notion information from image sequence in order to perform the data compression, the field rate conversion, and the motion compensated interpolation effectively. It is well known that the location of the smallest sum of absolute difference(SAD) does not always give the true motion vector(MV) since the MV obtained via full block search is often corrupted by noise. In this paper, we first classifies the input blocks into 3 categories : the background, the shade-motion, and the edge-motion. According to the characteristics of the classified blocks, multiple locations of relatively small SAD are searched with an adaptive search window by using the proposed method. The proposed method picks MVs among those candidates by using temporal correlation. Since temporal correlation reveals the noise level in a particular region of the video image sequence, we are able to reduce the search are very effectively.