• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.371-380
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• 2019

To identify the relationship between instructor's image and participation motive, this study conducted a research on 293 elderlies over 65 at 6 sports centers located in Seoul, Gyeonggi, and Incheon regions. The research results were as follows. First, in the image of instructor based on demographic characteristic, gender showed significant difference with instructor's talent while gender showed significant difference with instructor's talent, instructing image, and living image. Also, the sports type had significant difference with all subfactors of instructor image. Secondly, in the participation motive based on the demographic characteristic, gender showed significant difference with internal motive while age and sports type demonstrated significant difference with all subfactors of participation motive. third, the instructor image had significant influence on both internal and external motive. While instructing image and human relationship image had significant difference in internal motive, the external motive showed significant difference with instructor talent, living image, and human relationship image. thus, the research result showed that instructor's image is a significant variable which enhances elderly's motive for participating in life sports.

• Journal of the Korean Society of Costume
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• v.61 no.6
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• pp.101-112
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• 2011

The purpose of this study was to investigate the relationships among clothing image, make-up image, and hair image. The Data were collected from 306 women living in Gyeongnam province in June, 2009. Statistical analysis used in this study were frequency, F-test, t-test, Duncan test, factor analysis, Cronbach's ${\alpha}$, correlation coefficient, and multiple regression. The results of this study were as follows.: Three factors of clothing image were titled as elegance, youth, and visibility. Three factors of make-up image were titled as modern, romanticism, and mediocrity. Four factors of hair image were titled as attraction, individuality, gentleness, and cuteness. The clothing image, make-up image, and hair image according to the demographic characteristic of women showed significant difference. The clothing image resulted in correlation with the make-up image and hair image. The clothing image had a influence on the make-up image and hair image.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.11-24
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• 1990

This is the study about the meteorological satellite cloud image classification by objective methods. For objective cloud classification, linear discriminant analysis was tried. In the linear discriminant analysis 27 cloud characteristic parameters were retrieved from GMS infrared image data. And, linear cloud classification model was developed from major parameters and cloud type coefficients. The model was applied to GMS IR image for weather forecasting operation and cloud image was classified into 5 types such as Sc, Cu, CiT, CiM and Cb. The classification results were reasonably compared with real image.

• The Research Journal of the Costume Culture
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• v.18 no.5
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• pp.1003-1016
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• 2010

The purpose of this study is to reorganize any rusty image including natural modeling characteristic presented from the natural phenomenon to certain patterns in order to create the fashion design that are valued in the expansion of independently expressional area and modeling art. As a method for research, the author analyzed the concept and characteristic for rust with a base of theoretical background by the documental research and realistic consideration, analyzed its modeling characteristic through domestic and overseas pictures, and e-documents as data, inspected the modeling activities of various categories that various images were adapted related to rust, looked into the concept of Digital Textile Printing and its producing procedure as an expressional method, and analyzed the examples of modern dress and its ornament making use of Digital Textile Printing. The conclusions of this study are as below. First, the rust occurred due to the natural phenomenon is the bond with different material like metal, each unique modeling characteristic occurs and harmony of various patterns has abundant aesthetic value. Second, the author could endowed sensible characteristic and speciality with works and could produce creative fashion design that painting, abstractive pattern and harmony of unique sense of colors are significant by using the image of rust, Third, to emphasize natural feeling of rust, the author could develop creative design that simple silhouette and impressive pattern look significant by reorganizing and applying rust according to repetition, increment, rhythm, contract, emphasis and harmony. Fourth, Digital Textile Printing method is used to induce visual effect by the expression of feels of rust, and the author could express the natural patterns, delicate expression for the feels of a material and unique design of emotion.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.75-81
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• 2014

In a distribution of the digital image, there is a serious problem that is distributed an illegal forgery image by pirates. For the problem solution, this paper proposes an image forensic decision algorithm using an edge energy information of forgery image. The algorithm uses SA (Streaking Artifacts) and SPAM (Subtractive Pixel Adjacency Matrix) to extract the edge energy informations of original image according to JPEG compression rate(QF=90, 70, 50 and 30) and the query image. And then it decides the forge whether or not by comparing the edge informations between the original and query image each other. According to each threshold in TCJCR (Threshold by Combination of JPEG Compression Ratios), the matching of the edge informations of original and query image is excused. Through the matching experiments, TP (True Positive) and FN (False Negative) is 87.2% and 13.8% respectively. Thus, the minimum average decision error is 0.1349. Also, it is confirmed that the performed class evaluation of the proposed algorithm is 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic) curve is 0.9388 by sensitivity and 1-specificity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.23-30
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• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.457-458
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• 2002

The fractal dimension is the characteristics that can quantitatively define the irregularity in natural. It is useful in describing the morphology or various rubbed surface for hydraulic piston motor instead of the stylus profiling method. But fractal parameters had not constructed on the morphological characteristic or rubbed surface because of the insufficient knowledge about a conception of fractal dimension. In this study, for the purpose or applying fractal I parameters practically, we have suggested way to establish the morphological characteristic of rubbed surface with fractal parameters, and we carried out an experiment on the lubricant friction and wear by using Ball-ON-Disk type tester. Materials were the brass and the bronze which are used to slipper-pad in the hydraulic piston motor. We searched for fractal parameters or surface structure with the digital image processing, Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Using the image processing and fractal parameters for rubbed surface in the friction and wear test, morphology of rubbed sur race can be effectively obtained by fractal dimensions.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.193-199
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• 2002

Analyzing working conditions with shape characteristics of wear debris in a lubricated machine, it can be effect on diagnosis of hydraulic machining system. And it can be recognized that results are processed threshold images of wear debris. But, in order to predict and estimate a working condition of lubricated machine, it is need to analysis a shape characteristic of wear debris and to identify. Therefor, If shape characteristics of wear debris are identified by computer image analysis and the neural network, it is possible to find the cause and effect of wear condition. In this stud)r, wear debris in the lubricant oil are extracted by membrane filter $(0.45{\mu}m)$, and the quantitative value of shape characteristic of wear debris are calculated by the digital image processing. This morphological information are studied and identified by tile artificial neural network. The purpose of this study is to apply morphological characteristic of wear debris to prediction and estimation of working condition in hydraulic machining systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.407-412
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• 2012

This study investigated the process of thermal-induced growth of micro-crack developed at the crystalline solar cell using EL image, determined the output characteristic according to the pattern of micro-crack, analyzed the I-V characteristic according to the pattern of crack growth, and predicted the output value using simulation. The purpose of this study was, therefore, to investigate the process of thermal-induced growth of micro-crack developed at the early stage of PV module completion using EL image, to analyze the resulting decrement of output and predict the output value using simulation. It was observed that the crack grew increasingly by the thermal condition, and accordingly the lowering of output was accelerated. The output values of crack patterns with various direction were predicted using simulation, resulting in close I-V curve with only around 4% of error rate. It is considered that it is possible to predict the electric characteristic of solar cell module using only pattern of micro-crack occurred at solar cell based on our results.