• Fashion & Textile Research Journal
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• v.17 no.3
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• pp.315-326
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• 2015

Woman leadership has been remarkably highlighted with women's accelerating entry into society. Domestic and overseas interests about political leaders began with the age of media and they are rapidly spreading worldwide with the development of internet, SNS and blog. Along with this phenomenon, exposure of images has been remarkably increasing and fashion has been also used as a political strategy. However, the research on woman political leaders has been insufficient so this study selected Geunhye Park, Michelle Obama and Hillary Clinton as representative woman leaders for the research. 149 pictures of Geunhye Park, 171 pictures of Michelle Obama and 124 pictures of Hillary Clinton from the articles containing their pictures from Jan. 2002 to Dec. 2013 were analyzed, focusing on their gender. The three woman political leaders' typical images of femininity, masculinity and androgyny were categorized respectively and the period and works in which those images had been expressed were reviewed. Also, fashion styles of the images pursued by each gender were analyzed through their color, material, silhouette, design point, items and accessories. As a result, Geunhye Park had femininity image at the beginning and had masculinity image when she did election campaigns, which led to her current image of androgyny. Michelle Obama uses the image of femininity, masculinity and androgyny simultaneously. It was found that Hillary Clinton emphasized the image of masculinity and androgyny but she emphasizes femininity image these days.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1787-1793
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• 2018

Shadow is a common phenomenon observed in natural scenes, but it has a negative influence on image analysis such as object recognition, feature detection and scene analysis. Therefore, the process of detecting and removing shadows included in digital images must be considered as a pre-processing process of image analysis. In this paper, the existing methods for acquiring 1D invariant images, one of the feature elements for detecting and removing shadows contained in a single natural image, are described, and a method for obtaining 1D invariant images based on linear regression has been proposed. The proposed method calculates the log of the band-ratio between each channel of the RGB color image, and obtains the grayscale image line by linear regression. The final 1D invariant images were obtained by projecting the log image of the band-ratio onto the estimated grayscale image line. Experimental results show that the proposed method has lower computational complexity than the existing projection method using entropy minimization, and shadow detection and removal based on 1D invariant images are performed effectively.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.427-435
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• 2012

The aim of this study is to investigate facial temperature changes induced by facial expression and emotional state in order to recognize a persons emotion using facial thermal images. Background: Facial thermal images have two advantages compared to visual images. Firstly, facial temperature measured by thermal camera does not depend on skin color, darkness, and lighting condition. Secondly, facial thermal images are changed not only by facial expression but also emotional state. To our knowledge, there is no study to concurrently investigate these two sources of facial temperature changes. Method: 231 students participated in the experiment. Four kinds of stimuli inducing anger, fear, boredom, and neutral were presented to participants and the facial temperatures were measured by an infrared camera. Each stimulus consisted of baseline and emotion period. Baseline period lasted during 1min and emotion period 1~3min. In the data analysis, the temperature differences between the baseline and emotion state were analyzed. Eyes, mouth, and glabella were selected for facial expression features, and forehead, nose, cheeks were selected for emotional state features. Results: The temperatures of eyes, mouth, glanella, forehead, and nose area were significantly decreased during the emotional experience and the changes were significantly different by the kind of emotion. The result of linear discriminant analysis for emotion recognition showed that the correct classification percentage in four emotions was 62.7% when using both facial expression features and emotional state features. The accuracy was slightly but significantly decreased at 56.7% when using only facial expression features, and the accuracy was 40.2% when using only emotional state features. Conclusion: Facial expression features are essential in emotion recognition, but emotion state features are also important to classify the emotion. Application: The results of this study can be applied to human-computer interaction system in the work places or the automobiles.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.677-684
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• 2016

With the increase of multimedia information such as image, researches on extracting high-level semantic information from low-level visual information has been realized, and in order to automatically generate this kind of information. Various technologies have been developed. Generally, image retrieval is widely preceded by comparing colors and shapes among images. In some cases, images with similar color, shape and even meaning are hard to retrieve. In this article, in order to retrieve the object in an image, technical value of middle level is converted into meaning value of middle level. Furthermore, to enhance accuracy of segmentation, K-means algorithm is engaged to compute k values for various images. Thus, object retrieval can be achieved by segmented low-level feature and relationship of meaning is derived from ontology. The method mentioned in this paper is supposed to be an effective approach to retrieve images as required by users.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1149-1155
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• 2012

In this paper, we propose cause diagnosis method of semiconductor defects from semiconductor industrial images. Our method constructs feature database (DB) of defect images. Then, defect and input images are subdivided by uniform block. And the block similarity is measured using histogram kai-square distance after color histogram calculation. Then, searched blocks in each image are merged into connected objects using clustering. Finally, the most similar defect image from feature DB is searched with the defect cause by measuring cluster similarity based on features of each cluster. Our method was validated by calculating the search accuracy of n output images having high similarity. With n = 1, 2, 3, the search accuracy was measured to be 100% regardless of defect categories. Our method could be used for the industrial applications.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.160-171
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• 2006

In this paper, we propose a face detection method using region segmentation to deal with complex images that have various environmental changes such as mixed background and light changes. To reduce the detection error rate due to background elements of the images, we segment the images with the JSEG method. We choose candidate regions of face based on the ratio of skin pixels from the segmented regions. From the candidate regions we detect face regions by using location and color information of eyes and eyebrows. In the experiment, the proposed method works well with the images that have several faces and different face size as well as mixed background and light changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1194-1199
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• 2009

Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color and brightness information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.393-402
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• 2007

The purpose of this study is to provide the design direction based on consumer sensitivity through the structure between product design preferences - sensitivity image - design elements. For the purpose, we selected men's shaver products for this study subject and collected 164 shavers' pictures released between 2001-2007 years. Then, we carried out a pilot test for collection of sensitivity images about shavers, made a survey using semantic differential method and analyzed the survey. According the result, consumers preferred the sensitivity images "luxury, attractive, stable", design elements satisfied the preference images were "form of body is not a circular arcs or a polygon, material is steel, button is push style, and a color of body is not brown." This study can provide a base of the causal relationship between design preferences - sensitivity image - design elements and a design process to predict consumer sensitivity-oriented design.

• Journal of IKEEE
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• v.24 no.1
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• pp.97-105
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• 2020

A thermal imaging sensor receives the radiating energy from the target and the background, so it has been widely used for detection, tracking, and classification of targets at night for military purpose. In recognizing the target automatically using thermal images, if the correct edges of object are used then it can generate the classification results with high accuracy. However since the thermal images have lower spatial resolution and more blurred edges than color images, the accuracy of the classification using thermal images can be decreased. In this paper, to overcome this problem, a new hierarchical classifier using both shape and local features based on the segmentation reliabilities, and the class/pose updating method for vehicle classification are proposed. The proposed classification method was validated using thermal video sequences of more than 20,000 images which include four types of military vehicles - main battle tank, armored personnel carrier, military truck, and estate car. The experiment results showed that the proposed method outperformed the state-of-the-arts methods in classification accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.59-67
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• 2002

Recently, much demand of vector data have increased rapidly such as a digital map instead of traditional a paper map and the raster data such as a high-resolution orthoimage have been used for many GIS application with the advent of industrial high-resolution satellites and development of aerial optical sensor technologies. Aerial photogrammetric technologies using an airship can offer cost-effective and high-resolution color images as well as real time images, different from conventional remote sensing measurements. Also, it can acquire images easily and its processing procedure is short and simple relatively. On the other hand, it has often been used for the production of a small-scale land use map not required high accuracy, monitoring of linear infrastructure features through mosaicking strip images and construction of GIS data. Through this study, the developed aerial photogrammetric system using the airship expects to be applied to not only producing of scale 1:5, 000 digital map but also verifying, editing, and updating the digital map which was need to be reproduced. Further more, providing the various type of video-images, it expects to use many other GIS applications such as facilities management, scenery management and construction of GIS data for Urban area.