• 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 KIISE:Software and Applications
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• v.29 no.11
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• pp.818-825
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• 2002

Depth information is one of the most important factor for the recognition of a digital face image. Range images are very useful, when comparing one face with other faces, because of implicating depth information. As the processing for the whole fare produces a lot of calculations and data, face images ran be represented in terms of a vector of feature descriptors for a local area. In this paper, depth areas of a 3 dimensional(3D) face image were extracted by the contour line from some depth value. These were resampled and stored in consecutive location in feature vector using multiple feature method. A comparison between two faces was made based on their distance in the feature space, using Euclidian distance. This paper reduced the number of index data in the database and used fewer feature vectors than other methods. Proposed algorithm can be highly recognized for using local depth information and less feature vectors or the face.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.55-64
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• 1999

In this paper, new gamut-mapping algorithm (GMA) that utilizes variable anchor points (center of gravity on the luminance axis) is proposed. The proposed algorithm increases luminance range, which is reduced from conventional gamut mapping toward an anchor point. In this process, this algorithm utilizes multiple anchor points with constant slopes to both reduce a sudden color change on the gamut boundary of the printer and to maintain a uniform color change during the mapping process. Accordingly, the proposed algorithm can reproduce high quality images with low-cost color devices.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.87-94
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• 2005

3D image mosaicking is useful for 3D visualization of the roadside scene of urban area by projecting 2D images to the 3D planes. When a sequence of images are filmed from a side-looking video camera passing long distance areas, the ghost effect in which same objects appear repeatively occurs. To suppress such ghost effect, the long distance range areas are detected by using the distance between the image frame and the 3D coordinate of tracked optical flows. The ghost effects are suppressed by projecting the part of image frames onto 3D multiple planes utilizing vectors passing the focal point of frames and a virtual focal point. The virtual focal point is calculated by utilizing the first and last frames of the long distance range areas. We demonstrate algorithm that creates efficient 3D Panoramic mosaics without the ghost effect at the long distance area.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.193-197
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• 2003

Radar target identification can be achieved by using various radar signatures, such as one-dimensional(1-D) range profile, 2-D radar images, and 1-D or 2-D scattering centers on a target. In this letter, five 1-D scattering center extraction methods are discussed - TLS(Total Least Square)-Prony, Fast Root-MUSIC (Multiple Signal Classification), Matrix-Pencil, GEESE(GEneralized Eigenvalues utilizing Signal-subspace Eigenvalues), TLS-ESPRIT(Total Least Squares - Estimation of Signal Parameters via Rotational Invariance Technique), These methods are compared in the context of estimation accuracy as well as a computational efficiency using a noisy data. Finally these methods are applied to the target classification experiment with the measured data in the POSTECH compact range facility.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1286-1301
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• 2003

This paper introduces segmentation based environment modeling method and integration method using multiple environment map for constructing the realtime image-based panoramic navigation system. The segmentation-based environment modeling method is easy to implement on the environment map and can be used for environment modeling by extracting the depth value by the segmentation of the environment map. However, an environment model that is constructed using a single environment map has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the environment map occurs due to the occlusion. In this paper, we suggest environment models integration method using multiple environment map to resolve the above problem. This method can express parallax effect and expand the environment model to express wide range of environment. The segmentation-based environment modeling method using multiple environment map can build a detail model with optimal resolution.

• Radiation Oncology Journal
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• v.35 no.2
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• pp.101-111
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• 2017

The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.

• The Research Journal of the Costume Culture
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• v.12 no.3
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• pp.379-391
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• 2004

The purpose of this study was to examine the effects of uniform's color and motif on nurse's impression formation. The experimental design was 5×3×2(uniform color×motif ×perceiver's gender) factorial design with a between-subjects design. The experimental materials developed for the study were a set of stimuli and a response scale. The subjects were 738 undergraduate students of Daejon and Chungnam province. The SPSS package was used for data analysis which includes factor analysis, two-way ANOVA, Duncan's multiple range test, and Cronbach's α to measure the reliability. Results were as follows; The image or the stimulus was consisted of the 4 different dimensions(evaluation, sociability, ability, potency). All the independent variables showed some significant impression effects on selected dimensions. The motif and perceiver's gender also showed significant main effects as well as some interaction effects with the color variable on some selected impression dimension and the impression effects of the three variables in relationship to perceiving nurses' images. On a conclusion, these results supported the Gestalt theory.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.1
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• pp.59-71
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• 2016

To obtain more accurate approximation of the true images in the deblurring problems, the weighted global generalized cross validation(GCV) function to the inverse problem with multiple right-hand sides is suggested as an efficient way to determine the regularization parameter. We analyze the experimental results for many test problems and was able to obtain the globally useful range of the weight when the preconditioned global conjugate gradient linear least squares(Gl-CGLS) method with the weighted global GCV function is applied.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.166-173
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• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.