• Smart Structures and Systems
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• v.33 no.5
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• pp.349-358
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• 2024

Structural digital models can be effectively established by spatially obtaining digital images using an unmanned aerial vehicle (UAV). One of the main purposes of the structural digital modeling is computer vision-based exterior damage detection of a target structure. To investigate micro-scale damage from the digital model, high-resolution digital images obtained with a close-up vision survey is typically required. However, serial image synthesis such as image stitching may cumulate stitching errors as the number of scanned images increases. Therefore, in this paper, a novel loop closure-based digital image stitching technique is proposed and experimentally validated using the close-up surveyed digital images acquired from an in-situ dam structure located in South Korea. The test results reveal that the proposed technique outperforms a non-loop closure-based image stitching technique, which can cause serious distortions, such as ghosting and vanishing phenomena.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.295-301
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• 2004

Satellite captures images periodically and economically over the area wider than aerial photographs, and reconnaissance to unapproachable area. For these advantages, mapping using high resolution satellite image has high potentials of marketability and development. Therefore, utilization of satellite image in mapping and GIS is expected to be growing and research on describable feature, positional accuracy and, possible mapping scale is urgently needed. This research presented that Quick Bird orthoimage could be used to update digital map on a scale of 1:5,000. Quick Bird image was corrected geometrically based on ground control points. DEM was generated using height data of digital topographic map. The orthoimge was produced by digital differential rectification based on DEM which was generated using height data of digital topographic map(scale 1;5,000 and 1;1,000). When the digital topographic map was overlaid with the orthoimage, it was very easy to find changed region or new features builded after the map compiled.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1209-1211
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• 2003

The wavelet and semivariogram analysis method are used to identify the city landscape and farmland landscape pattern on the 1m resolution IKONOS images. The results prove that wavelet method is a potential way for landscape pattern analysis. Compared to semivariogram analysis, Wavelet analysis can not only detect the overall spatial pattern, but also find multi-scale and direction structures. In this experiment, the wavelet analysis results indicate: (1) the city landscape image is mainly composed of three level structures whose spatial pattern characters appear at 2m, 16m, 128m and 256m accordingly; (2) the farmland landscape is mainly two scale spatial patterns appearing at the 2m, 128m and 256m. IKONOS Remote sensing, with the high spatial and spectral information, is a powerful tool that can use in many ecological systems research and sustainable management.

• Journal of the Korean Society of Industry Convergence
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• v.12 no.4
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• pp.221-228
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• 2009

This study analyzes the behaviors and images of city residents on the six Gyeongsangbuk-do rural theme villages. The results of analysis bring the following conclusions. 1) Behaviors of city residents are related with the images on rural villages. In addition, the better the image is, the higher their behaviors' needs. 2) Behaviors' needs become higher on the village as the image on 'Scale type' becomes better. 3) Especially, in case of Gimcheon and Gyeongju, we find a strong relationship between the images of 'Scale type' and 'Magnificent type' and behaviors; these villages should raise the scale and standard of villages by certain point.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.203-210
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• 2021

Deep leaning convolutional neural networks (CNN) have successfully been applied to image super-resolution (SR). Despite their great performances, SR techniques tend to focus on a certain upscale factor when training a particular model. Algorithms for single model multi-scale networks can easily be constructed if images are upscaled prior to input, but sub-pixel convolution upsampling works differently for each scale factor. Recent SR methods employ multi-scale and multi-path learning as a solution. However, this causes unshared parameters and unbalanced parameter distribution across various scale factors. We present a multi-scale single-path upsample module as a solution by exploiting the advantages of sub-pixel convolution and interpolation algorithms. The proposed model employs sub-pixel convolution for the highest scale factor among the learning upscale factors, and then utilize 1-dimension interpolation, compressing the learned features on the channel axis to match the desired output image size. Experiments are performed for the single-path upsample module, and compared to the multi-path upsample module. Based on the experimental results, the proposed algorithm reduces the upsample module's parameters by 24% and presents slightly to better performance compared to the previous algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.5
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• pp.597-606
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• 1998

The purposes of the study were 1) to evaluate the visual image of colored Korean traditional dress for woman 2) to analyze the colors and, color combinations effect on the image perception using gestalt theory. The research method was a quasi-experimental with a between subjects design. The experimental materials developed for the study were a set of stimuli and a response scale. The stimuli was consisted of 17 drawings of females wearing Korean tradinational dress, by using CAD simulation. A response scale consisted of semantic differential scales. The subjects were 1138 undergraduate students of Taejon city, Chungnam province and Chungbuk province. Their responses to the semantic differential scales were analyzed using factor analysis, one-way ANOVA, Duncan's multiple range test, 1-test. Results were as follows; 1) The image of the stimulus was consisted of the 4 different dimensions.(sociability, evaluation, visibility, attractiveness) 2) Clothing colors had significant effects on image perception of the evaluation dimension, visibility dimension and attractiveness dimension in the mono-color set. The blue showed the most positive image on the evaluation dimension, and the yellow and the gray showed negative image on the same dimension. The yellow showed the most salient image and the gray showed the least salient image on the visibility dimension. The red showed the most attractive image and the green showed the least attractive image on the attractiveness dimension. 3) In hi-color set stimulus, the perceived image was influenced by color combinations. The yellow blouse-the red skirt set showed the most sociable image on the sociability dimension. The blue blouse-the green skirt set showed the most positive image on the evaluation dimension. The yellow blouse-the red skirt set showed the most salient image and the blue blouse-the green skirt set showed the least salient image on the visibility dimension. And the red blouse-the yellow skirt set showed the most attractive image on the attractiveness dimension. On conclusion the visual image of Korean traditional dress wearer was affected by dress colors and color combinations.

• Journal of KIISE
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• v.42 no.6
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• pp.764-768
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• 2015

Requirement of effective image handling methods such as image retrieval has been increasing with the rising production and consumption of multimedia data. In this paper, a method of constructing more effective descriptor is proposed for robust keypoint based image retrieval. The proposed method uses information embedded in the first order and second order derivative images, in addition to the scale space image, for the descriptor construction. The performance of multi-image descriptor is evaluated in terms of the similarities in keypoints with a public domain image database that contains various image transformations. The proposed descriptor shows significant improvement in keypoint matching with minor increase of the length.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.2
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• pp.318-327
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• 2005

The purpose of this study was to analyze the image perception of modern fashion according to erotic expressions ans erotic levels. The research methods werea quasi-experimental research. The experimental materials developed for the study were a set of stimuli and a responsse scale. The stimuli was consisted of 15 photographs according to erotic expressions and erotic levels. The reponse scale consisted of semantic differential scales. The subjects consisted of 254 male and 260 female undergraduate students of Chungnam National University by a convenient sampling method. The data were analyzed by factor analysis, ANOVA, Duncan's multiple range test and t-test. Result were as follows ; 1) The fashion image of erotic experessions and levels, were categorized into 3 images factors : sexy-potency, modesty, attractiveness. 2) The erotic expressions significantly affected on three image factors 3) The erotic levels showed significant differences in three image dimensions and stronger erotic levels pressented more sexy-potency, less models and attractive images. 4) The erotic expressions showed interaction effects with the erotic levels in three image dimensions. 5) Subject's gender had a significant difference on fashion image perception : male subjects perceived the fashion photographs more attractive than female subjects did.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.35-40
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• 2010

Skyline extraction in mountainous images which has been used for navigation of vehicles or micro unmanned air vehicles is very hard to implement because of the complexity of skyline shapes, occlusions by environments, dfficulties to detect precise edges and noises in an image. In spite of these difficulties, skyline extraction is avery important theme that can be applied to the various fields of unmanned vehicles applications. In this paper, we developed a robust skyline extraction algorithm using two-scale canny edge images, topological information and location of the skyline in an image. Two-scale canny edge images are composed of High Scale Canny edge image that satisfies good localization criterion and Low Scale Canny edge image that satisfies good detection criterion. By applying each image to the proper steps of the algorithm, we could obtain good performance to extract skyline in images under complex environments. The performance of the proposed algorithm is proved by experimental results using various images and compared with an existing method.

• Journal of Sensor Science and Technology
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• v.12 no.6
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• pp.258-264
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• 2003

The present paper studies how to calibrate hydrometer using image process. The method aligns particular scales of hydrometer selected for calibrating the hydrometer with the horizontal plane of the reference liquid automatically without man's operation. Major parts composing the system are CCD camera, frame grabber, stepping motor and image process program. The image process program is composed of a part that locates the meniscus and aligns it with a scale and a part that controls the step motor. To verify the performance of the developed method, this study compares the meniscus and scale observed directly with the naked eye with the result of calibration by the manual calibration method. The differences between the corrections were less than $0.004\;kg/m^3$ with uncertainty of $0.06\;kg/m^3$. These showed that the calibration results of the developed hydrometer calibration using image process nearly equal to manual method.