• Journal of Fashion Business
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• v.6 no.4
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• pp.163-172
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• 2002

The purpose of this study is to investigate purple image and formative properties in contemporary fashion. For the study of formative properties 152 kinds of costume samples from photographs in fashion magazines. For the study of image 40 kinds of costume samples is used and divided into tones : pale(Vp, Lgr, L), bright(P, B), vivid(S, V, Dp), dark(Gr, Dl, Dgr, Dk). A total 24 pairs of abjective words were used to measure the semantic differential scale in this study. The data were analyzed by factor analysis, ANOVA, MDS and regression analysis. The results are as follows; 1. Factor analysis has extracted 5 factors which consist of purple image in contemporary fashion. The factors are high quality, hardness and softness, simplicity, temperature, maturity. 2. There were significant differences in visual evaluation of purple tones. 3. The discrimination among. 4 purple tones was related to weight of purple 4. The evaluative dimensions of purple image in modern fashion were identified by Light - Heavy and Pale - Strong. 5. The image effect on Preference, Buying needs, Pleasant and Riches was consist of complicated sensibility.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.4
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• pp.1-8
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• 2023

This study is meaningful in figuring out how much the Korean people's awareness of hanok has increased even though interest in hanok has also increased due to the Korean Wave craze. Therefore, with respect to the exterior of hanok, which is visually recognized first, the level of experts and ordinary people is grasped through a semantic discrimination scale, and the degree of visual recognition is to be investigated centering on the color image of hanok buildings. This is the process of thinking about how the Korean image should be reflected in the design, and we want to suggest the direction that modern hanok should go. The study compared and analyzed the difference in visual color based on the elevation of the hanok using a 7-point and 5-point scale method for the general public and experts, and utilized the IRI adjective vocabulary scale and the color matching image scale to construct new hanoks with insufficient differences in appearance and shape. It can be applied to design and image preservation and construction of existing hanok.

• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.493-500
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• 2002

Fingerprint recognition is concerned with fingerprint acquisition and matching. Our research was focused on a fingerprint matching method using an inkless fingerprint input sensor at the fingerprint acquisition step. Since an inkless fingerprint sensor produces a digital-image-processed fingerprint image, we did not consider noise that can happen while acquiring the fingerprint. And making the user attempt fingerprint input as random, we considered image distortion that translation and rotation are included as complex. NJTC algorithm is used for fingerprint identification and verification. The method to find the center of the fingerprint is added in the NJTC algorithm to supplement discrimination of fingerprint recognition. From this center point, we decided the optimum cropping size for effective matching with pixels and demonstrated that the proposed method has high discrimination and high efficiency.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• Journal of the Ergonomics Society of Korea
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• v.13 no.1
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• pp.37-46
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• 1994

The accurate error size and discrimination region in the perception of depth amount from 3-dimensional images by the human visual system will be the basic data for the utilization and application of the binocular 3- eimensional image system. This paper is focused on studying the accuracy of the depth amount perceived from 3- dimensional images by the human visual system. From the performed experiment, the following results have been obtained: (1) The depth amount perceived from the binocular 3- dimensional images has been displayed by a proper scale of distance, and found to be imprecise and also have a large variance. (2) In utilizing the binocular 3-dimensional image system, it seems more appropriate to make the images viewed outward rather than inward from the screen in the regard of error and variance. (3) The binocular 3-dimensional image system can be effectively applied to displaying unreal space, for example, the layout of room in design, from the viewpoint of perception characteristics of depth amount.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.7
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• pp.976-986
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• 2000

The purpose of this study is to clarify the relationship between the visual sensibility and the decorative design of clothing. 41 kinds of costume samples have been selected from photographs in fashion magazines under detail and trimming, and divided into three types according to line, shape, and form. I have measured these images by using Semantic Differential method. The obtained data were analyzed by factor analysis ANOVA, discriminant analysis, regression analysis and MDS. The results of analysis are as follow; 1. Factor analysis has extracted five factors which consist of decorative design sensibility. These factors are Attractiveness, Hardness and Softness, Rhythm, Decorativeness, Cuteness. 2. There were significant differences in visual evaluation of decorative design and demographics 3. The discrimination among formative designs was closely related to decorative image, especially between line and form. 4. The Image effect on Preference, Buying needs, Riches and Pleasant was consist of complicated sensibility. 5. Evaluative dimensions of decorative design were identified by Simple-Complicated, Cubic -Plane perceptive image differed in degree of similarity in spite of same formative design.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.38-46
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• 1996

This paper discusses the feasibility of Ultrasonic Nondestructive Evaluation (UNDE) technique for sport weld quality. Ultrasonic c-scan image assisted by image processing technique was used for Nondestructive Evaluation(NDE) of spot weld quality. Ultrasonic testing results obtained were confirmed and compared by Optical Microscope and SAM(Scanning Acoustic Mircroscope) observation of the spot-weld cross section, The results show that the nugget dinameter can be successfully measured with the accuracy of 0.5mm. It was ascertained that ultrasonic c-scan technique is very effective method for the sake of the approach to the quantitative measurement of nugget diameter and the discrimination of the corona bond from nugget. Additional support for the above conclusions is provided by the results for galvanized steel. The ultrasonic results for galvanized welds generally correspond to the results for uncoated steel. Finally, it was found that the above-mentioned technique can be sufficiently applied to NDE method for securing the Quality Assurance(QA) of spot welded products in production line.

• Proceedings of the ESK Conference
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• 1994.04a
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• pp.19-31
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• 1994

The accurate error size and discrimination region in the perception of depth amount from 3- dimensional images by the human visual system will be the basic data for the utilization and application of the binocular 3 - Dimensional image system. This paper is focused on studying the accuracy of the depth amount perceived from 3-dimensional images by the human visual system. From the performed experiment, the following results have been obtained: (1) The depth amount perceived from the binocular 3-dimensional images has been displayed by a proper scale of distance, and found to be imprecise and also have a large variance. (2) In utilizing the binocular 3-dimensional image system, it seems more appropriate to make the images viewed outward rather than inward from the screen in the regard of error and variance. (3) The binocular 3- dimensional image system can be effectively applied to displaying unreal space, for example, the layout of room in design, from the viewpoint of perception characteristics of depth amount.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.397-398
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• 2007

In this paper, we have verified the applicability of the line-clustering segmentation method to steel-tube X-ray images. Image data is partitioned into three regions on the base of vertical line edge detection. Parameters for necessary condition, such as neighborlity, similarity and directional neighbor correlation coefficients, proposed in that method is calculated and applied to such selected regions separately Segmental features at each region is extracted statistically and functional classification is clustered by the point or space process. The analyzed data and experimental results show that the line-clustering segmentation method has a high applicability to X-ray image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.897-904
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• 2005

Face Recognition has been an active research area because it is not difficult to acquire face image data and it is applicable in wide range area in real world. Due to the high dimensionality of a face image space, however, it is not easy to process the face images. In this paper, we propose a method to reduce the dimension of the facial data and extract the features from them. It will be solved using the method which extracts the features from holistic face images. The proposed algorithm consists of two parts. The first is the using of principal component analysis (PCA) to transform three dimensional color facial images to one dimensional gray facial images. The second is integrated linear discriminant analusis (PCA+LDA) to prevent the loss of informations in case of performing separated steps. Integrated LDA is integrated algorithm of PCA for reduction of dimension and LDA for discrimination of facial vectors. First, in case of transformation from color image to gray image, PCA(Principal Component Analysis) is performed to enhance the image contrast to raise the recognition rate. Second, integrated LDA(Linear Discriminant Analysis) combines the two steps, namely PCA for dimensionality reduction and LDA for discrimination. It makes possible to describe concise algorithm expression and to prevent the information loss in separate steps. To validate the proposed method, the algorithm is implemented and tested on well controlled face databases.