• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.3_4
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• pp.483-490
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• 2004

By using the formerly established SERVQUAL Model, measurement methods and determinant variables in the other papers for the Service Quality, this study first focuses to find out the difference consumers' evaluation between before-experience and after-experience of the educational service, and second, to examine the difference consumers' evaluation between before-experience and after-experience of the educational service according to pre-recognition degree for the subjected educational service quality. The results are derived as follows. 1. As a consequence of the simulation, the consumers distinctly tend to recognize importance of human concern and visual aspect after experience of educational service. 2. Between the group with more pre-recognition degree and less pre-recognition degree for the subjected educational service quality, have no difference.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.82-91
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• 2013

This paper proposes a building recognition algorithm using watershed image segmentation algorithm and integrated region matching (IRM). To recognize a building, a preprocessing algorithm which is using Gaussian filter to remove noise and using canny edge extraction algorithm to extract edges is applied to input building image. First, images are segmented by watershed algorithm. Next, a region adjacency graph (RAG) based on the information of segmented regions is created. And then similar and small regions are merged. Second, a color distribution feature of each region is extracted. Finally, similar building images are obtained and ranked. The building recognition algorithm was evaluated by experiment. It is verified that the result from the proposed method is superior to color histogram matching based results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.2
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• pp.8-17
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• 2000

In this work, two approaches were proposed for the recognition of partial discharge patterns. The first approach was neural network with backpropagation algorithm, and the second approach was angle calculation between t재 operator vectors. PD signals were detected using three electrode systems; IEC(b), needle-plane and CIGRE method II electrode system. Both of neural network and angle comparison method showed good recognition performance for the patterns similar to the trained patterns. And the number of operators to be used had a great influence on the recognition performance to the untrained patterns.

• Journal of the Korean Home Economics Association
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• v.41 no.4
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• pp.71-83
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• 2003

The purpose of this research is to analyse the factors affecting household's educational expenditure on on-line educational system, student's recognition of better remarks effect, and satisfaction of on-line educational system. The sample of this study was 484 parents who had experiences of using on-Une educational system for their children being from preschool to high school. The results were as follows ; First, the household's educational expenditure on on-line educational system was affected from the sex, children's school level, and using on-line educational system or not. Second, the significant variables which affected students' recognition of better remarks effect were husbands' job, number of children, the first child's school level, households' monthly expenditure, students' remarks at school, and using on-line educational system or not. Third, the satisfaction of on-line educational system was affected from husband's job, using on-line educational system or not, and the students' recognition of better remarks effect.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.685-688
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• 2000

In this paper, we used image information for the enhancement of Korean numeral speech recognition. First, a noisy environment was made by Gaussian generator at each 10 dB level and the generated signal was added to original Korean numeral speech. And then, the speech was analyzed to recognize Korean numeral speech. Speech through microphone was pre-emphasized with 0.95, Hamming window, autocorrelation and LPC analysis was used. Second, the image obtained by camera, was converted to gray level, autocorrelated, and analyzed using LPC algorithm, to which was applied in speech analysis, Finally, the Korean numerial speech recognition with image information was more ehnanced than speech-only, especially in ‘3’, ‘5’and ‘9’. As the same LPC algorithm and simple image management was used, additional computation a1gorithm like a filtering was not used, a total speech recognition algorithm was made simple.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.873-876
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• 2000

The information-theoretic approach to face recognition is based on the compact coding where face images are decomposed into a small set of basis images. Most popular method for the compact coding may be the principal component analysis (PCA) which eigenface methods are based on. PCA based methods exploit only second-order statistical structure of the data, so higher- order statistical dependencies among pixels are not considered. Independent component analysis (ICA) is a signal processing technique whose goal is to express a set of random variables as linear combinations of statistically independent component variables. ICA exploits high-order statistical structure of the data that contains important information. In this paper we employ the ICA for the efficient feature extraction from face images and show that ICA outperforms the PCA in the task of face recognition. Experimental results using a simple nearest classifier and multi layer perceptron (MLP) are presented to illustrate the performance of the proposed method.

• Journal of the Korean Institute of Rural Architecture
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• v.7 no.3
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• pp.27-35
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• 2005

This study is about finding out characteristic of recognition individual housing in seaside of Donghae. To accomplish this purpose, we survey the 150 houses related to the landscape. Thus the major analysis is to take basic data, such as image(modern, western, traditional, etc) about exterior form of housing corresponding to the landscape. The result summarized as follows First, the elements for the characteristic of recognition were exterior material finish, exterior color, roof type, roof material finish, window size, roof slope, area of wall vs roof. Second, the image of traditional housing was very insufficient to plan landscape of housing with design elements. This research suggests that landscape housing of future is to be environmental landscape design and the proper design is to be various considering not only user's preference but also control of landscape.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.674-675
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• 2022

In this paper, we present a DPS (FPGA)-based object recognition method that can recognize objects (pedestrians, bicycles, motorcycles) located in the vehicle's blind spot while the vehicle is stopped or driving at low speed and has a fast object recognition performance of 30 frames per second.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• The Journal of Information Systems
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• v.19 no.4
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• pp.137-165
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• 2010

The government and enterprises have interest in the green IT products, therefore this study focus on the green IT products. First, we study the effects on the purchase intention of the green IT products by perceived value, perceived quality, and perceived trust. Second, we consider the environmental characteristics such as environmental concern, green recognition, and environmental knowledge. Third, we study the moderating effects of environmental characteristics. The proposed model was empirically tested using data collected from users having the purchase intention of the Green IT products. The major results of this study are as follows. First, perceived value and perceived trust had a positive effect on purchase intention of the green IT products. Second, environmental concern, green recognition, and environmental knowledge had moderating effects between perceived value and purchase intention of the green IT products. Third, environmental concern and green recognition had moderating effects between perceived trust and purchase intention of the green IT products. This study can provide many implications for government and businesses considering green IT products.