• Journal of the Korean Home Economics Association
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• v.39 no.2
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• pp.73-84
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• 2001

The purposes of this study were 1) to identify the effect of clothing benefit sought on fashion image sought and 2) to determine the effects of fashion image and benefit sought on purchase intention of Gal-ot. The data were collected via a self-administered questionnaire from 172 female tourist(20 to 50 ages) in Cheju and analyzed by factor analysis, stepwise multiple regression analysis and logistic regression analysis. Four factors of benefit sought were identified : Practicality/economic-value, aesthetics, reputation, and souvenir-value. Six factors of fashion image were found and labeled as: Sexy/feminine, wild/mannish, easy/simple, Cheju image, ecology and natural image. The effects of benefits sought(Practicality/economic-value, aesthetics, reputation and souvenir-value) on fashion image(Sexy/feminine, easy/simple, Cheju and natural image) were found. There were also significant effects of benefit sought(souvenir-value) and fashion image(Cheju image) on purchase intention of Gal-ot.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.101-106
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• 1997

A method is proposed to generalize the image transformation from an image to another one according to a pair of example images. When an original image and its target image are given, the unknown image transformation from the original image to the target one in automatically approximated by a sequence of several known image transformation filters by the method. The target image is assumed to be generated manually by using a drawing software. In this method, the order of image transformation filers is regarded as the chromosome of a virtual living thing and is evolved according to Genetic Algorithm. This method can be applied to automatic construction of expert systems for image processing.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.8
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• pp.1119-1130
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• 1999

The purpose of this was to investigate the differences in recognition of brand and advertisement image according to the life style segments of adolescents. The subjects selected for the final analysis were 613 female high school students whoe were residents in Seoul Pusan and Taejeon. The statistics used for data analysis were factor analysis one-way ANOVA Duncan's multiple range test paired t-test frequency distribution and percentage by the SPSS program The results of this study were as follows : 1. The life style of adolescents wee classified into five groups : Sports Uninterest group Friend Preference/Fashion Uninterest group Sports Preference/Home Oriented group Fashion Interest group and Confidence group. 2, The brand image and advertisement image recognition didn's correspond in general 3. The brand image and advertisement image recognition were significantly different among five groups of life style. The Confidence group and Friend Preference/ Fashion Uninterest group recognized brand image and advertisement image lower than the other groups.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.6-10
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• 2020

Unlike modern photography technology, in the early days, efforts to physically compose an image with a concept similar to the current photograph have not been popular or commercially successful. The limitation of the use of images as artistic media or recordings has reached the stage of introducing the technology of image analysis to automate the function that humans recognize and judge through vision. In addition, the accuracy of the image has exceeded the human visual ability, enabling the technology that enables the step of recognizing and informing the fact that the human is not aware of it. Based on such a base, the range that can be applied through the image data in the future era can be said to be unpredictable, and the technology that targets large scale image database instead of an image is also expanding the possibilities as a new application technology. In order to identify a particular image from a massive database, different methodologies have been introduced. In this paper, we discuss image identifier production methods based on multi-resolution pyramid.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.48-54
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• 2011

As personal or compact devices with image acquisition functionality are becoming easily available for common users, the voluminous images that need to be managed by image related services or systems demand efficient and effective methods in the perspective of image identification. The objective of image identification is to associate an image with a unique identifier. Moreover, whenever an image identifier needs to be regenerated, the newly generated identifier should be consistent. In this paper, we propose three image identifier generation methods utilizing image features: linear component, luminance area, and combination of both features. The linear component based method exploits the information of distribution of partial lines over an image, while the luminance area based method utilizes the partition of an image into a number of small areas according to the same luminance degree. The third method is proposed in order to take advantage of both former methods. In this paper, we also demonstrate the experimental evaluations for uniqueness and similarity analysis that have shown favorable results.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.365-372
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• 2000

he paper introduces evolutionary computing to Fractal Image Compression(FIC). In Fractal Image Compression(FIC) a partitioning of the image into ranges is required. As a solution to this problem there is a propose that evolution computation should be applied in image partitionings. Here ranges are connected sets of small square image blocks. Populations consist of $N_p$ configurations, each of which is a partitioning with a fractal code. In the evolution each configuration produces $\sigma$ children who inherit their parent partitionings except for two random neighboring ranges which are merged. From the offspring the best ones are selected for the next generation population based on a fitness criterion Collage Theorem. As the optimum image includes duplication in image data, it gets smaller in saving space more efficient in speed and more capable in image quality than any other technique in which other coding is used. Fractal Image Compression(FIC) using evolution computation in multimedia image processing applies to such fields as recovery of image and animation which needs a high-quality image and a high image-compression ratio.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.436-439
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• 2004

Most of past image processing systems have been designed independent of image contents. Now, evolving computation power is making the "image-dependent" elegant algorithms possible to get the better image renditions on display. This paper introduces our recent approaches to quality and pleasant imaging based on image-dependent. Three typical approaches to comfortable "Sharpness", "Lightness", and "Color" renditions on display image arc presented.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.187-190
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• 2007

This study is for analyzing best band in image matching using correlation coefficient of left and right images of stereo image pair, lot red, green, blue band images separated from color aerial photo and gray image converted from the same color aerial photo image. The image matching is applied to construct Digital Elevation Model(DEM) or terrain data. The correlation coefficients and variation by change of pixel patch size are computed from pixel patches of which sizes are $11{\times}11{\sim}101{\times}101$. Consequently, the correlation coefficient in red band image is highest. The lowest is in blue band. Therefore, to construct terrain data using image matching, the red band image is preferable. As the size of pixel patch is growing, the correlation coefficient is increasing. But increasing rate declines from $51{\times}51$ image patch size and above. It is proved that the smaller pixel patch size than $51{\times}51$ is applied to construct terrain data using image matching.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.370-376
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• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1494-1496
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• 2007

This paper deals with image quality analysis considering the impact of psychological factors involved in assessment. The attributes of image quality requirement were partitioned according to the visual perception characteristics and the preference of image quality were obtained by the factor analysis method. The features of image quality which support the subjective preference were identified, The adequacy of image is evidenced to be the top requirement issues to the display image quality improvement.