• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.4
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• pp.87-99
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• 2022

The purpose of this study is to develop machine embroidery textile designs for each technique that can be expressed using a single-headed computer embroidery sewing machine through a machine embroidery CAD system. For research, embroidery CAD utilized the Artistic digitizer, and the guillotine computer-mechanical magnetization machine used ELNA. The design concept was limited to portraits and relics of independence activists in six memorial halls built in Korea. The results of this study are as follows. First, it was found that the machine embroidery texture, which could only be produced by industries in the past, can be expand in the infinite creative embroidery design area by enabling the digitalization of motif images and the simulation of machine embroidery techniques through various layout options. Second, in the development of machine embroidery textures, it was found that the setting of the width, height, axis ratio, stitch, object, path, length, density, layer order, etc. in embroidery CAD is a very important part of determining the completeness of the embroidery results. Third, mechanical embroidery textile designs, which can be represented by single-head computer machine embroidery machine were able to show colorful embroidery results that differs from the original image by using seven main techniques and five deep technique alone or in combination, according to the designer's intention.

• ETRI Journal
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• v.45 no.5
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• pp.847-861
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• 2023

Dynamic object detection is essential for ensuring safe and reliable autonomous driving. Recently, light detection and ranging (LiDAR)-based object detection has been introduced and shown excellent performance on various benchmarks. Although LiDAR sensors have excellent accuracy in estimating distance, they lack texture or color information and have a lower resolution than conventional cameras. In addition, performance degradation occurs when a LiDAR-based object detection model is applied to different driving environments or when sensors from different LiDAR manufacturers are utilized owing to the domain gap phenomenon. To address these issues, a sensor-fusion-based object detection and classification method is proposed. The proposed method operates in real time, making it suitable for integration into autonomous vehicles. It performs well on our custom dataset and on publicly available datasets, demonstrating its effectiveness in real-world road environments. In addition, we will make available a novel three-dimensional moving object detection dataset called ETRI 3D MOD.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.937-946
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• 1995

We proposed and efficient block segmentation and classification method for the document analysis using SGLDM(spatial gray level dependence matrix) and BP (back Propagation) neural network. Seven texture features are extracted directly from the SGLDM of each gray-level block image, and by using the nonlinear classifier of neural network BP, we can classify document blocks into 9 categories. The proposed method classifies the equation block, the table block and the flow chart block, which are mostly composed of the characters, out of the blocks that are conventionally classified as non-character blocks. By applying Sobel operator on the gray-level document image beforebinarization, we can reduce the effect of the background noises, and by using the additional horizontal-vertical smoothing as well as the vertical-horizontal smoothing of images, we can obtain an effective block segmentation that does not lead to the segmentation into small pieces. The result of experiment shows that a document can be segmented and classified into the character blocks of large fonts, small fonts, the character recognigible candidates of tables, flow charts, equations, and the non-character blocks of photos, figures, and graphs.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of the Korean Society of Costume
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• v.40
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• pp.151-170
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• 1998

The purpose of this study is to examine the value of grotesque fashion and to predict the future fashion trend. The grotesque originates the formative art. It emerges towards of a century or transitional period in most case. In particular, it was used as the expressive method of an individual's inside and a satire on society through the work of artists in the Middle Age, the renaissance, the sym-bolism, the dadaism, the surrealism, the pop art, the technology art, and the post-modernism, etc. The grotesque in fashion is represented in the work of avant-garde fashion designers who lead the high fashion. The grotesque fashion which was combined with an image of non-formality, non-rationality, an absurdity and reality. It has been begun shape of female dress in the renaissance. Afterwards, it was represented in extremely exaggerated and distorted pop art, hippies' fashion in the 1960's. In the 1970's, it was reflected in genderless rock star and destructive punk fashion. It was also represented in the androgynous fashion which was combined with both sexes, the goth/gothic fashion which was expressed with a realistic and fanciful shape and the tattoo of skin-head in the 1980's. In the 1990's, the grungy look which was dirty and the cyber punk fashion. In general, it was also expressed by the avant-garde fashion designers. To sum up, a grotesque fashion which is expressed by experimental designers is classified into four shapes. 1, Union of some extraneous is expressed as different kinds of fashion theme, such as abnormality of texture, uses of surrealistic elements and chaos of sex. Although it appears that the abnormal union of grotesque has only discord and collision, it also shows a feeling of freedom for the tension. 2. Introduction of real and fanciful image is expressed as a cyborg, realistic description of disgusting animal skin and aggressive shape. Especially, it is worth while to notice Tierre Mugler and Alexander Macqueen's work which expressed the shape of mingling human of Middle Age. 3. distortion or exaggeration is expressed as an unformed shape, the exaggeration of a clothing size, the abnormal exaggeration of human body and the ignorance of clothing form. 4. Introduction of a disgusting image is expressed as an extremity of reality, motifs of death, clothing material of disgusting hair and the ostentation of sex. Motto which leads modern fashion is something new and shocking. The grotesque fashion is an expression of eagerness for something new. It often show something ironic in the form of humor which is embedded in an abnormal and shocking pattern. The grotesque fashion is represented as an extreme beauty. It will stand as an important element of the future fashion and as a particular style with the change and fluidity.

• Korean Journal of Environment and Ecology
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• v.22 no.3
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• pp.289-300
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• 2008

This study aims to discriminate differences in natural landscapes between the Cairngorms National Park in Scotland and the Jirisan National Park in Korea, using functions of content-based image retrieval such as texture, shape, and color. Digital photographs of each National Park were taken and selected. The low-level functions of photographic images were reduced to orthogonally rotated five factors. Based on the reduced factors, a linear decision boundary was obtained between Cairngorms landscapes and Jirisan landscapes. As a result, the discriminant function significantly delineated two groups, resulting in $x^2=63.40$ with df=5(p<0.001). Both the eigenvalue 2.417 and the value of wilks' lambda 0.29 supported that the most proportion of total variability came from the differences between the means of discriminant function of groups. It was estimated that four independent variables explained about 70.7% of total variance of dependent variable. The variable with the largest effect on landscapes was far region-related factor(r=1.07), followed by near region-related factor (r=0.90). A total of 90.7% of cross-validated grouped cases were correctly classified. It was interpreted that far distant regions, as well as near distant regions, had sufficient discrimination power for landscape classification between the Cairngorms National Park and the Jirisan National Park, so that landscape identity of the National Park over cultures was revealed by skylines in a most effective way. Relatively fewer factors making visual landscapes were effectively used to classify natural landscapes of the National Parks which had different semantics.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.184-193
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• 2010

This paper proposes a biological iridescence BRDF(Bidirectional Reflectance Distribution Function) compression and rendering method. In the graphics technology, iridescence sometimes is named structure colors. The main features of these symptoms are shown transform of color and brightness by varying viewpoint. Graphics technology to render this is the BRDF technology. The BRDF methods enable realistic representation of varying view direction, but it requires a lot of computing power because of large data. In this paper, we obtain reflection map from iridescence BRDF, analyze color of reflection map and propose representation method by several colorfully concentric circle. The one concentric circle represents beam width of reflection ray by one normal vector. In this paper, we synthesize rough concentric by using several virtually optical normal vectors. And we obtain spectrum information from concentric circles passing through the center point. The proposed method enables IBR(image based rendering) technique which results is realistic illuminance and spectrum distribution by one texture from reduced BRDF data within spectrum.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.2
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• pp.231-250
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• 2014

This study considers types of design expression and examines aesthetic characteristics by analyzing images shown on clothes worn by Korean First Ladies. This study is to accumulate a fundamental database for the effective style coordination for images of First Ladies and future directions of clothing design. The types of design expression on the clothes of Korean First Ladies are as follows. First, in terms of silhouette, H line and A line is generally represented on the silhouette of clothes; in addition, the H line is highly expressed on the silhouette. The keyword of images by design types are generally feminine, elegant on the silhouette of First Ladies' clothing, and represented a progressively more modernized image on the silhouette. Second, in terms of color, it is expressed diverse images on the color of First Ladies' clothing, and exceptionally the tendency of elegant image is highly charged on the color of clothes. This sort of tendency is influenced by the preferences of First Ladies; subsequently, most First Ladies wear their clothes with a high brightness and chroma. Third, in terms of materials, the image of elegant and simple is highly expressed through First Ladies' clothes and it is caused by choosing the clothes of a plain texture rather than a visible and fancy one. The aesthetic characteristics based on an analysis of the types of design expression on the clothes of Korean First Ladies are as follows. First, 'femininity' on First Ladies' clothes is expressed by A line silhouette of a feminine curve and decorative effects. Second, 'simplicity' on First Ladies' clothes is expressed on the H line silhouette of a straight figure or through the solid colors of high chroma. Third, 'elegance' on First Ladies' clothes is represented on the silhouette of a restrained curve, long skirt hemlines, and woolen fabric with a neat, warm and soft coordination of colors. Forth, 'traditionality' on First Ladies' clothes is expressed through the application of materials and colors that influence culture, traditions, and detailed decorativeness.