• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.210-216
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• 2014

The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.48-56
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• 2006

This paper introduces design and implementation of digital photo kiosk system, digital photo printing system, with auto color correction module that considers gamut between touch screen and output device, digital photo printer, to provide user-preferred media. This module performs media correction function to service high quality contents for image captured by digital camera and mobile phone camera. Since it is implemented as LUT for real-time processing, the system offers one-touch interface to user. As a result of implementation, this kiosk system provides user-favorite photo because of black and white mode, sepia mode, and brightness and contrast adjustment. Also it can gives smooth tone transition and photos of similar color to captured image due to auto color correction module.

• Journal of the Korea Fashion and Costume Design Association
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• v.7 no.2
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• pp.101-110
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• 2005

Vivienne Westwood could be placed in a unique position in the contemporary fashion design. She has never belonged in a core group of mainstream fashion designer but not been always in an outsider position. She got from mainstream fashion designer circles enormous appreciation, even established fashion industry was influenced by her fashion design. She began her fashion design with rebellious T-shirts like 'destroy' T-shirt, chicken-bone T-shirt, and nipple-zipper T-shirt, all of which revealed her disgust against establishment. All these T-shirts testify her total negation tendency in her youth. However, she did not continue to keep such a kind of total negation attitude against establishment In 1980s she changed her political attitude towards establishment, and this change also found a reflection in her fashion design. In her pirate-collection the dark image of her fashion in the 1970s changed into a totally different bright image with full of gold colour. Although this collection had radiated brightness, it contained still outsider character from mainstream fashion design. The following fashion design in 1980s and 1990s evolved further on the line of Pirate-collection, but they continued to contain certain outsider characteristics. Vivienne Westwood kept some kind of anti-establishment attitude, and this attitude more or little came to the surface of her design. She was always political and critical to the establishment. In 2005, in her 64, she designed a liberty T-shirt, which showed her political attitude and her engagement in social issues. Also it showed the change from the early total negation to the constructive critical affirmation. In this paper the relation between the fashion design of Vivienne Westwood and her political attitude and the influence of her political attitude to her fashion design is analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.27-32
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• 2012

In this paper, we propose a fuzzy method that improves the existing problem of the fuzzy filtering algorithm. The proposed fuzzy filtering algorithm separates R, G, and B channels from the color image. Mask information was extracted from separated channels and the brightness of the mean value and median value for channels was applied in the function of the proposed fuzzy method to calculate the membership and achieve application in the inference rule. Also, the membership degrees of R, G, and B were used to distinguish the possibility of noise. The proposed fuzzy method selected three membership functions. If noise is distinguished, the noise is eliminated by selecting the median value or mean value as the relevant pixel value according to the degree of noise. By applying the proposed method in color images, it was verified that the proposed method is more effective in eliminating noise when compared with the conventional fuzzy filtering method.

• Geophysics and Geophysical Exploration
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• v.6 no.1
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• pp.7-12
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• 2003

The lineament extraction from satellite images is important in the geologic studies including groundwater and mineral exploration, groundwater survey, natural hazard analysis, and many others. The lineaments in remote sensing images are identified by the difference of pixel values or brightness. Since the visual interpretation is apt to be influenced by the knowledges and experiences, many of the automatic lineament detection algorithms are developed to ensure the objectives and efficient outputs. DSTA (dynamic segment tracing algorithm) is one of such algorithms, which can be applied to not only mountainous area but also alluvial area. However, when the alluvial area is wider than mountain region, somewhat severe noises are generated. To reduce such noises, AERA (alluvial effect reducing algorithm) is proposed and tested for the image which contains mountains, cultivated land and urban area. Upon the application of AERA, alluvial effects in lineament extraction from satellite image are substantially reduced.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.1
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• pp.1-9
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• 2003

To evaluate the quantitative nature of laser fluorescence(LF) and dye-enhanced laser fluorescence(DELF) on early enamel caries, artificial caries were induced on the bovine enamels and argon laser was irradiated on the surfaces of lesions. Fluorescence radiance from enamel specimen was recorded with CCD camera which was connected to PC image analyzing system. The difference of fluorescence of radiance(DFR) between the carious and the sound enamel in each sample of the LF and the DELF groups were measured by image analyzing program. The DFR of lesion surfaces measured with laser fluorescence and lesion depths were evaluated and the results are as follows: The caries lesions were discriminated from sound enamels by the darkness with LF and by the brightness with DELF. The DELF was more sensitive than the LF at the earlier stage of demineralization.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.63-70
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• 2012

In medical image processing field, object recognition is usually processed based on region segmentation algorithm. Region segmentation in the computing field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2-map information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2-map as seed points for 2D region growing and final boundary correction to enable region segmentation even when the border line was not clear. As a result, an average area difference of 7.5%, which was higher than the accuracy of conventional exist region segmentation algorithm, was obtained.

• Proceedings of the IEEK Conference
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• 2001.10a
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• pp.111-116
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• 2001

Waste office paper, photocopied or laser printed, has recently increased along with office automatization. In waste office paper, toner ink is used as the printing medium in place of conventional oil ink. Since toner ink cannot be saponificated by alkali and be decolored by bleaching, different from the case of oil ink, toner remains on regenerated paper as black specks. Although cascade recycling of waste office paper is compelled at present, the demand for low-grade paper is limited. From such circumstances, a new separation process for waste office paper is demanded to achieve parallel recycling. At the first stage of separation studies, the sharpness of separation is evaluated using small separators to obtain fundamental data. In a lab-scale separator, the sample amount of one feed is generally a few grams. However, the sample amount used for brightness, ERIC, and image analysis that are generally used to evaluate the efficiency of deinking are not small for lab-scale tests of these analyses. This paper describes an investigation of a sheet preparation method by a small amount of sample under 0.5g and compares the precision of toner content determination of spectroscopic analysis and image analysis from the viewpoint of separation evaluation. The easiness and convenience of the operation using only general-purpose equipments has also been set as a principle purpose. From the viewpoint of an analysis that yields high precision with a small amount of sample in short time, the method calculating the absorption coefficient from diffuse reflectance in the visible region is the most rational method in this study.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.7-12
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• 2018

In today's rapidly growing contemporary society, there is a tendency for demand to automate production processes by utilizing the vision system. In general, image recognition is mainly concerned with embossed characters such as license plates, and research on recognition of intaglio characters is very limited. Especially, intaglio characters, which are marked on rubber related products such as tire surfaces, have difficulty in recognizing characters or numbers through image because the difference in brightness with surrounding is not so large. In this paper, we propose a system to improve the recognition rate of characters marked on intaglio rubber products such as tire surfaces. Also, it can be applied flexibly according to the lighting environment. Through the proposed system, production and inventory management and defect detection can be processed quickly by applying to the production process of tire and rubber products.