• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• The Research Journal of the Costume Culture
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• v.12 no.1
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• pp.59-72
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• 2004

The objectives of this study were to investigate the perceptions of Korean female university students for clothing pattern tendency and structural element of clothing pattern image dimension and to find how individual personality type influence the preferred clothing pattern characteristics. For this study, a questionnaire was designed and sent to 600 female university students of Daejeon, Seoul and metropolitan area. The tool used in this study was MBTI(The Myers-Briggs Type Indicator) Form G Korean version and for the analysis of data SPSS 10.0 package were used. 10 representative patterns for this study were floral, dot, stripe, check, animal, abstract & artistic, geometric, vegetable & leaf, paisely, patchwork pattern. The data were analyzed by factor analysis, arithmetic mean, One-Way ANOVA, x²-test. The major findings were as follows: Clothing pattern image dimension perceived by Korean female university students for 10 representative patterns were basic form, deluxe, specialty, and cultural dimension. Among them, basic form and deluxe dimension were major dimensions. In basic form dimension, dot pattern score was high indicating female students perceive it as light, comfortable, clean, cool and simple pattern image. In deluxe dimension, floral pattern scored high and in specialty dimension, abstract and artistic pattern scored high among other pattern image. In cultural dimension, geometric pattern and check pattern scored high. Based on other detailed analysis results, It is concluded that the personality type greatly influence clothing pattern evaluation. For example, in case of color combination of patchwork pattern, there was a difference in color preference depend on a personality type such as sensing(S) or intuition(N). Therefore, sensing personality type preferred adjacent color combination than contrast color combination. Detailed marketing strategy is necessary in planning textile design of merchandise plan.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1209-1211
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• 2003

The wavelet and semivariogram analysis method are used to identify the city landscape and farmland landscape pattern on the 1m resolution IKONOS images. The results prove that wavelet method is a potential way for landscape pattern analysis. Compared to semivariogram analysis, Wavelet analysis can not only detect the overall spatial pattern, but also find multi-scale and direction structures. In this experiment, the wavelet analysis results indicate: (1) the city landscape image is mainly composed of three level structures whose spatial pattern characters appear at 2m, 16m, 128m and 256m accordingly; (2) the farmland landscape is mainly two scale spatial patterns appearing at the 2m, 128m and 256m. IKONOS Remote sensing, with the high spatial and spectral information, is a powerful tool that can use in many ecological systems research and sustainable management.

• Proceedings of the KSRS Conference
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• v.2
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• pp.764-767
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• 2006

It can be important framework data to monitor the change of land-use pattern of river boundary in design and management of river. This study analyzed the change of land-use pattern of Gab- and Yudeung River using time-series aerial images. To do this, we carried out radiation and geometric correction of image, and estimated land-use changes in inland and floodplain. As the analysis of inland, the ratio of residential, commercial, industrial, educational and public area, that is urbanized element, increases, but that of agricultural area shows a decline on the basis of 1990. Also, Minimum Distance Method, which is a kind of supervised classification method, is applied to extract water-body and sand bar layer in floodplain. As the analysis of land-use, the ratio of level-upped riverside land and water-body increases, but that of sand bar decreases. These time-series land use information can be important decision making data to evaluate the urbanization of river boundary, and especially it gives us goodness in river development project such as the composition of ecological habitat.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.197-202
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• 2016

This paper suggested that medical image database construction technique that generated and recognized from variable medical device and professional medical experts for the formalization and pattern extraction from informal medical images. And then we transformed informal image characteristics to digital data, and generated the meaningful pattern matching informations. Through this experienced works, so many related researchers can easily access the medical images database and use this formalized image informations on the variable fields.

• Transactions of the Society of Information Storage Systems
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• v.8 no.2
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• pp.67-71
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• 2012

Page-oriented holographic data storage (HDS) is very sensitive to the tilt error. Therefore, tilt error should be measured and compensated. Especially, mechanical tilt measurement method cannot cope with tilt error measurement because photopolymer medium has shrinkage problem. Therefore, the method to solve this problem is using the reconstructed image which can represent both tilt and shrinkage effect. In this paper, we suggest disc tilt measurement algorithm using image pattern of retrieval data.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.8
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• pp.1001-1010
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• 1998

The purpose of this study was to investigate the images and characteristic formative elements of Korean traditional patterns. The Korean pattern image could be interpreted into visual elements of design based on the images, the characteristic formative elements of Korean traditional patterns, and their relationships. Fourteen patterns selected from 5 groups of Korean patterns were used as stimuli. An image evaluation using a 2-point sementica scale of 19 bipolar adjectives, and an impression evaluation of which results were presented by visual drawing using lines and shapes were carried out. The data were analyzed by correspondence analysis and cluster analysis. The major findings are as follows; 1. Fourteen patterns and 19 adjectives were marked on a perception map composed of two (x and y-) axes. The bipoles of x- and y axes were soft-hard and splendid-artless, respectively. 2. Four clusters semerged to account for the dimensional sturucture of 14 patterns and 19 adjectives. These were splendid image, soft image, individualistic image, and sophisticated image. However there was no pattern which belonged to the cluster, sophisticated image. The Korean pattern image was founded to be better related to the kind of patterns than the type of patterns. 3. The characteristic formative elements obtained from the impression test were contour of motif, repeated line or shape, various curved lines, and decorative elements. 4. The splendid image was related to Bongwhang patterns and detailed line and complexity. The individualistic image was related to the abstractive form of Bongwhang pattern and the decorative form of Cloud pattern both of which have the characteristics of point-symmetry and abstraction, and Turtle-back pattern. In this case, the related charac-teristic formative element was identified to be repeated lines. The soft image was related to Moran, Cloud, and Taegeuk patterns. The related characteristic elements were various types of curved lines, decorative elements, and rounded contours.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.509-511
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• 2004

This paper outlines the development of image processing system, which will allow the general users in Government and Public organizations easily to use and apply KOMPSAT EOC images in their own business. The system includes an import/export module of EOC image distributed in Hierarchical Data Format (HDF) file and various image processing analysis modules. Especially, the image mosaic and subset functions are designed to use EOC image as an image map, generating the Ortho-image module. To update the various spatial data with EOC image, some essential modules such as change detection by pattern recognition, overlay between images and vector data, and modification of vector data are implemented in the system. The system is developed based on the user request analysis of government agency, and suited for more efficient use of satellite image in public applications. Such system is expected to contribute to practical application of KOMPSAT-2 that will be launched in 2005. Further efforts will be made to accommodate the KOMPSAT -2 MSC data.

• Journal of the Korean Society of Costume
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• v.18
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• pp.269-281
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• 1992

The purposes of this study were to 1) classify the contents of clothing image preferences, 2) find out the relationship among personal values, preferences for clothing image and clothing design, and 3) investigate the relationship between clothing image preferences and clothing design preferences, Questionnaire was comprised of three section. The clothing image preference measure was included 36 bipolar adjectives of 7-point scales. Clothing design preferences measure was included the items of patterns, colors, and textures. 'Survey of Personal Values' by Eung-Un Hwang and Kyung -hye Lee was used for measurement of 6 values : practical mindedness ; achievement ; variety ; decisiveness; orderliness; and goal orientation. Samples were 288 college women. The data were analyzed using pearson's correlation coefficient and factor analysis. The results of the study were the following. 1. Four segments of clothing image preferences derived by factor analysis : F. 1 'progressive-conservative' ; F.2. 'casual-formal'; F.3 'plain-splendid'; F.4 'masculine-feminine'. 2. In relation between personal values and clothing image preferences, 1) achievement was positively related to the preference of progressive image 2) variety was positively related to the preferences of progressive and masculine image, and 3) goal orientation was negatively related to the preferences of the progressive and masculine image, and positively related to plain image. 3. In relation between personal values and clothing design preferences, 1) practical mindedness was positively related to the preference of black, 2) achievement was positively related to the preferences of blue and such realistic pattern as floral, 3) variety was positively related to the preferences of geometric or abstract patterns and thick or transparent texture, and 4) orderliness was negatively related to the preferences of abstract pattern. 4. In relation between clothing image preferences and clothing design preferences, 1) progressive image was positively related to abstract pattern, red, blue, and black, 2) casual image was positively related to geometric pattern, green, blue, and negatively related to red and soft rexture, 3) plain image was negatively related to lustered and transparent texture, abstract pattern, red, and black, and 4) masculine image was negatively related to lustered, thin, soft, and transparent texture, floral and dotted patterns, red, orange, and yellow.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.797-803
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• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.