• Korean Journal of Mathematics
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• v.14 no.1
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• pp.47-55
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• 2006

This paper presents an image analysis technique using connected components by applying SPA (shortest path algorithm) from graph theory. Software implementation of Floyd-Warshall transitive matrix labelling method is discussed. Results are also presented.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.4
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• pp.17-27
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• 2017

This study analyzes the trends of photo image components and forms of expression in global fashion advertising photos. First, photo image components are classified into seven categories: location (indoor-outdoor), the model's movement, pose, facial expression, gender, race and number of models. The forms of expression are classified into six categories: direct expression, sensual expression, symbolic expression, storytelling expression, dramatic expression, and sexual expression. With the aforementioned classifications, the trends were studied for three years from 2013 to 2015. The analysis result indicates the following: for the details of photo image components, the portion of indoor photos, static poses and conscious facial expressions was over 60% of the total for every season of the 3 years, while there was a slight increase in the number of models and the diversity of races. For the forms of expression, the sensual expression showed the largest portion accounting for over 50% of the total, followed by direct expression and storytelling expression. The findings from this study show that the trends of photo image components and forms of expression in global fashion advertisements are changing. Therefore, domestic companies will need to develop photo image components and forms of expression in line with the changing global fashion advertisement trends.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.155-164
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• 2015

In this paper, we propose a new color interpolation method based on trilateral filter approach, which not only preserve the high-frequency components(image edge) while interpolating the missing raw data of color image(bayer data pattern), but also immune to the image noise components and better preserve the detail of the low-frequency components. The method is the trilateral filter approach applying a gradient to the low frequency components of the image signal in order to preserve the high-frequency components and the detail of the low-frequency components through the measure of the freedom of similarity among adjacent pixels. And also we perform Gaussian smoothing to the interpolated image data in order to robust to the noise. In this paper, we compare the conventional demosaicing algorithm and the proposed algorithm using 10 test images in terms of hue MAD, saturation MAD and CPSNR for the objective evaluation, and verify the performance of the proposed algorithm.

• Journal of Fashion Business
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• v.18 no.4
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• pp.138-152
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• 2014

The purpose of this study was to examine the impact of personal image on self-leadership. The experimental study showed relationship between the variables of personal image and self-leadership by using personal image questionnaires and a revised self-leadership questionnaire both extracted from the literature study. The results of this study are as follows. First, six factors of self-leadership were drawn as the reliability and validity of were verified. The factors of self-leadership and the components for personal images showed a significant correlation. Second, the satisfaction rates of the components for personal image showed significant effects on three factors(performed successfully imagination, self-set goals, as well as belief and assumption analysis) of self-leadership. Third, significant results were obtained from the analysis of differences in self-leadership according to the levels of satisfaction on the components of personal image. These are expected to have effects on self-leadership between the groups for some factors(performed successfully imagination, self-set goals, belief and assumption analysis, self-reward, self-cues).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.223-229
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• 2018

This paper proposes a robust technique of image segmentation, which can be obtained if the topological persistence of each connected component is used as the feature vector for the graph-based image segmentation. The topological persistence of the components, which are obtained from the super-level set of the image, is computed from the morse function which is associated with the gray-level or color value of each pixel of the image. The procedure for the components to be born and be merged with the other components is presented in terms of zero-dimensional homology group. Extensive experiments are conducted with a variety of images to show the more correct image segmentation can be obtained by merging the components of small persistence into the adjacent components of large persistence.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1296-1305
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• 2019

To solve the problem of poor noise suppression capability and frequent loss of edge contour and detailed information in current fusion methods, an infrared and visible light image fusion method based on variational multiscale decomposition is proposed. Firstly, the fused images are separately processed through variational multiscale decomposition to obtain texture components and structural components. The method of guided filter is used to carry out the fusion of the texture components of the fused image. In the structural component fusion, a method is proposed to measure the fused weights with phase consistency, sharpness, and brightness comprehensive information. Finally, the texture components of the two images are fused. The structure components are added to obtain the final fused image. The experimental results show that the proposed method displays very good noise robustness, and it also helps realize better fusion quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1624-1632
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• 1996

Wavelet transform is widely used for high compression ratio image compression. It requeires a large memory when it is implemented by a hardware. Therefore, it is efficient to divide the entire image into blocks. Because the wavelet transform for divided blocks causes losses, pixels of the adjacent blocks are used. In the case of color image compression, the image is decomposed into brightness and color components, and then color components are downsampled. When the wavelet transform is performed by using pixels of adjacentblocks, the number of necessary pixels are doubled due to downsampling of color components. In this paper, we propose an efficient block wavelet transform using variablefilter length for brightness and color components. By using the proposed method, the number of pixels of adjacent blocks is optimized. We show the degradation of image quality due to the reduction of filter length for color components is negligible through simulations.

• The Research Journal of the Costume Culture
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• v.6 no.2
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• pp.203-216
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• 1998

In the study, conceiving that signifying processes like model, setting, advertisement and description are important to promote the purchase of clothes that would satisfy consumer's desire by their expressing mode, I considered the processes of components of which fashion ads consist. As for the methods to study, I regarded the results presented from prior researches of clothing & textiles and other disciplines for the components of fashion ads and objectified their image that may be interpreted subjectively: and then, I adopted to analyse them using advertisement-semiological method to make clear the signifying processes. The results are as follow: 1. Fashion ad, one of visual symbols to transfer brand image, conveys the image with which various components are combined like model, clothes, setting and description as signs. ① the image of clothes amy be differently expressed according to social, cultural norm and individual characteristics, in the case of clothes, therefore, the signified can be regarded as the transferred image by design of the clothes① sign, and the abstract conception which may be rise to mind by the image in a ceratin culture. ② Each signifier such as countenance, line of vision, attitude and hairstyle of a model conveys different image, or the signified, respectively, and it amy operate as a sign that can express the brand image symbolically. ③ The signifiers like background, color and property symbolize the advertised merchandise of clothes and define it attribute.. 2. In the case of fashion ads, key referent systems are fashion phenomena, contemporary role image, social psychology, common morality, and social, economical and milieu.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.520-525
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• 1992

This paper reports several mathematical properties of the filter vector developed for processing linearly-additive spatially-invariant image sequences. In this filtering of an image sequence into a single filtered image, the information about the image components originally distributed over the entire sequence is compressed into the one new image in a way that the desired component is enhanced and the undesired (interfering) components and noise are suppressed.