• Architectural research
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• v.12 no.2
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• pp.53-62
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• 2010

The purpose of this study is to examine design preferences for the sales spaces of duty-free shops (DFSs) by conducting image evaluations. The results will help improve quality by influencing designs for the construction, extension or remodeling of these shops. An image measurement method, the semantic differential method, was used to measure cognitive structure using photos of shops. Photos were collected of the DFS at Jeju Island, as well as photos of brand stores designed by architects. Two sets of 16 photos (32 different photos in all) were selected according to photo classification standards and design concepts, both decided by reviewing previous studies and related materials. The evaluation and survey were done by two sets of subjects: sales employees, who have experience and special knowledge of the evaluation of sales space; and students majoring in architecture. To strengthen the evaluation results, I conducted a preliminary survey and a main survey, verifying and complementing findings. 116 surveys were conducted, of which 14 were of poor quality and rejected, leaving and 102 to be analyzed. The collected surveys were statistically analyzed, using SPSS 12.0 for Windows. Reliability, image profile, factor and multi-dimensional scaling analyses were conducted. As a result, image evaluation structure and characteristics were obtained for sales spaces of DFSs, confirming the difference between them and other spaces.

• Korean Institute of Interior Design Journal
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• v.26 no.4
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• pp.93-102
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• 2017

The study of space through image evaluation has reached the stage of measuring the emotion with the development of IT technology and the advent of VR AR era. Many researches have been trying to evaluate the space and measure the emotion in objective form by providing various forms of spatial images such as photographs, sketches, and CG. In order for these studies to be used as objective data with logical relevance, it is necessary to describe in detail the method of collecting the data used in the experiment, the characteristics of the test procedure, and the method of analysis. This study is a basic study for constructing a database by systematically organizing the attributes, experimental methods and experimental procedures of subjects. From the viewpoint of securing the objectivity and reproducibility of the paper, we analyzed the spatial image evaluation process focusing on 1) evaluation subject, 2) experimental method, and 3) analysis standard. It is necessary to examine whether the object of evaluation and the form of image and the method of providing it meet the purpose of the study. In addition, the size and order of the image, the viewing time and the interval (break time) should be different according to the gender and group experiment and the individual test method.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.90-98
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• 2008

In recent, image data compression method of high resolution satellite image is the important issue for its application and development. The CCSDS (Consultative Committee for Space Data Systems) published a standard for the high resolution image data compression, CCSDS 122.0-B-1, in the end of 2005, which is expected to be widely applied in process of compression for the high resolution satellite images. In this paper, it is explained that the current trends of image compression methods for high resolution satellites, and then the comparison results between CCSDS 122.0-B-1 standard and JPEG are described.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.570-595
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• 2017

Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.263-265
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• 2003

The computation cost of image registration is affected by searching data size and space. This paper proposes an efficient image registration algorithm that uses multi-resolution wavelet decomposed image to reduce the data size search. The algorithm determines the correlation detection at low resolution on low-pass sub bands of wavelet and generate mask for higher resolution as part of a coarse to fine registration algorithm. The correlation matching is defined for coarse resolution similarity measurement, while mutual information (MI) is used at fine resolution. The results show that the new efficient mask-based algorithm improves computational efficiency and yields robust and consistent image registration results.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.1043-1051
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• 2007

The digital sun sensor calculates the incident sunlight angle using the sunlight image registered on a CMOS image sensor. In order to accomplish this, an exact center of the sunlight image has to be determined. Therefore, an accurate estimate of the centroid is the most important factor in digital sun sensor development. The most general method for determining the centroid is the thresholding method, and this method is also the simplest and easy to implement. Another centering algorithm often used is the image filtering method that utilizes image processing. The sun sensor accuracy using these methods, however, is quite susceptible to noise in the detected sunlight intensity. This is especially true in the thresholding method where the accuracy changes according to the threshold level. In this paper, a template method that uses the sunlight image model to determine the centroid of the sunlight image is suggested, and the performance has been compared and analyzed. The template method suggested, unlike the thresholding and image filtering method, has comparatively higher accuracy. In addition, it has the advantage of having consistent level of accuracy regardless of the noise level, which results in a higher reliability.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.368-374
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• 2010

Image segmentation is the basic step in the field of the image processing for pattern recognition, environment recognition, and context analysis. The Otsu's automatic threshold selection, which determines the optimal threshold value to maximize the between class scatter using the distribution information of the normalized histogram of a image, is the famous method among the various image segmentation methods. For the automatic threshold selection proposed by Otsu, it is difficult to determine the optimal threshold value by considering the sub-region characteristic of the image because the Otsu's algorithm analyzes the global histogram of a image. In this paper, to alleviate this difficulty of Otsu's image segmentation algorithm and to improve image segmentation capability, the original image is divided into several sub-images by using context fuzzy c-means algorithm. The proposed fuzzy Otsu threshold algorithm is applied to the divided sub-images and the several threshold values are obtained.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.194-197
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• 2000

Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.721-724
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• 1998

A circular image in a space don't appear as an exact circular image and appear as an oval in image buffer because distortion of camera lens, number of horizontal pixel of CCD photographing element and unmber of horizontal pixel of image buffer are not in accordance. By using familiar 3-D coordinate, know as circle's diameter, and cicle's center, you correct a pin-hole camera and get an exact circle with reprojection a circle into image buffer, according to a perspective.