• The Research Journal of the Costume Culture
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• v.17 no.6
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• pp.972-980
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• 2009

This study was aimed to develop ume flower image into a competitive fashion culture product image by reinterpreting the image in modern terms, manufacturing patterns and applying them to various items. In terms of method, ume flower petal was used as a motive and developed into a pattern, using Adobe Illustrator 10, a computer design program. Based on the symbolic image and realist form of ume flower, three new basic motives of new figurative image were set using form omission, simplification, overlapping, repetition and graphic elements. Each motive developed transformed patterns through the change, transformation, combination of colors. The repetitive unit of each motive set expressed geometrical patterns and combination of flower patterns using pattern repetition and $45^{\circ}$ repetition technique in combination with the check arrangement using quadrangle, and set the direction of design that would fit for each item of fashion culture products. Also, consistency and practicality were sought in the goods planning composition of each item by applying motive pattern results to the fashion culture goods, such as neckties, scarves, T-shirts that can be consumed in everyday life. It seems that more creative culture goods including ume flowers will be developed by seeing our own cultural elements as well as flower patterns like ume flower with modern trends.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.5
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• pp.915-929
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• 1996

The purpose of this study is to investigate the visual illusions and image of the combinated collars and sleeves which are combinated by the computer simulation. The detail object of this study as follows; 1) to know the visual illusions of the clothing as the collar and sleeves are combinated 2) to constract the clothing image using sementic differential scales 3) to know the differet image of the clothing as the collars and sleeves are combinted 4) to know the interaction effect of the collars and sleeves of the clothing The detail method of this study is as follows; In the first experiment, there are two groups; the first 8 groups are the combination of the same collar and the different sleeves. The second 8 groups are the combination of the same sleeve and the different collars. The second experiment has done for the 32 clothings which are the combination of the 8 collars and 4 sleeves. For the 14 clothing the image has tested by 13 semantic differential bi- polar scale. The subjects were 50 female students majoring in clothing and textile. The data analyzed by Kendall cofficient of concodance, Factor analysis, Anova and scheffe's test. Briefly the image of the clothing is much influenced by the varing of the collar than that of the sleeve. Thus, we also can conclude that the recognition of the clothing are much more dependent on the collar than sleeve.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.11
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• pp.1771-1781
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• 2008

The purpose of this study was to classify the casual image by clothing design elements. This research was done by survey method with 30 kinds of casual image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. Casual image was classified by 6 factors. Those were classic-casual, modern-casual, romantic-casual, vintage-casual, sexy-casual and active-casual images. 2. Classic-casual image was well-expressed by A silhouette, fit, chromatic and chromatic color coordinations and hard texture. Modern-casual image was well-expressed by H silhouette, fit and achromatic and achromatic color coordinations. Romantic-casual image was well-expressed by A silhouette, fit and soft texture. Vintage-casual image was well-expressed by H silhouette, combination apparel-fit, chromatic and chromatic color coordinations and fade-out texture. Sexy-casual image was well-expressed by fitted silhouette, tight apparel-fit and combination texture. 3. Casual image was positioned into mostly dynamic and modern on image scale.

• Journal of Fashion Business
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• v.12 no.5
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• pp.94-110
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• 2008

The main objective of this research was to understand the characteristics of separation color coordination of contemporary female fashion through the analysis of 'pre-a-porter Collections' of four collections (i. e. cities) - Paris, Milan, New York, London - from the periods of 2004 S/S to 2008/9 A/W. The data collection of 265 was done by reviewing 'pre-a-porter Collections' magazine and total 265 observations were made. Statistical analysis of frequency and also qualitative interpretation of separation color coordination characteristics were completed. The main findings were; (1) In separation color coordination of contemporary women's fashion collections, there were three main types of color scheme which were classified into seven detailed categories of color combination. First was the achromatic color & one chromatic separation color scheme which was classified into four categories of - black & white, black & grey, white & grey, and grey & grey - color combination. Second was the chromatic colors & one achromatic separation color scheme which classified into two categories of achromatic & chromatic color & one achromatic separation color combination, and chromatic colors & one achromatic separation color combination. Third was chromatic colors and one chromatic separation color combination. (2) The achromatic colors and one chromatic separation color scheme showed two phases of reinforcing the strong and modern image, or softening the hard and dull image of achromatic color combination. In color schemes which used more than two chromatic colors, the separation color frequently converted the tedious and monotonous fashion image, which caused by identical or similarity in color or tone harmony, into more attractive and interesting. (3) In conclusion, through the various use and coordination of various color schemes, color harmony and separation colors, the separation color coordination in contemporary female fashion has been suggested the effective way of color combination which can lead the visual pleasure and the vitality along with the unity and the harmony. This characteristics can create various images and visual diversity for fashion. The types and the use of color scheme and separation color showed different trends in four collections.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.3
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• pp.494-504
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• 2008

The purpose of this study was to classify the romantic image by clothing design elements. This research was done by survey method with 20 kinds of romantic image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. Romantic image was classified by 4 factors. Those were sexy-romantic, retro-romantic, natural-romantic and cute-romantic images. 2. Sexy-romantic image was well-expressed by fitted silhouette, achromatic and achromatic color coordinations and see-through texture. Retro-romantic image was well-expressed by X silhouette, achromatic and achromatic color coordinations and see-through or combination texture. Natural-romantic image was well-expressed by A silhouette and chromatic and achromatic color coordinations. Cute-romantic image was well-expressed by A silhouette and soft or combination(silky and soft) texture. 3. Romantic image was positioned into mostly traditional or artificial on image scale.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1205-1223
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• 2018

Image enhancement is an emerging method for analyzing the images clearer for interpretation and analysis in the spatial domain. The goal of image enhancement is to serve an input image so that the resultant image is more suited to the particular application. In this paper, a novel method is proposed based on Mamdani fuzzy inference system (FIS) using multiple fuzzy membership functions. It is observed that the shape of membership function while converting the input image into the fuzzy domain is the essential important selection. Then, a set of fuzzy If-Then rule base in fuzzy domain gives the best result in image contrast enhancement. Based on a different combination of membership function shapes, a best predictive solution can be determined which can be suitable for different types of the input image as per application requirements. Our result analysis shows that the quality attributes such as PSNR, Index of Fuzziness (IOF) parameters give different performances with a selection of numbers and different sized membership function in the fuzzy domain. To get more insight, an optimization algorithm is proposed to identify the best combination of the fuzzy membership function for best image contrast enhancement.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

• Korean Journal of Human Ecology
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• v.16 no.2
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• pp.407-419
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• 2007

The purpose of this study was to identify the effect of four clothing cues dot pattern size and ground field of color area ratio on dress's wearer image. The experimental materials developed for this study are a set of stimuli and response scales(The 7-point semantic). The stimuli were 30 color pictures manipulated with the combination of dot pattern size, dot pattern on background of color area ratio and neutral dress's using computer simulation. The subjects were 180 female undergraduates living students in Gyeong-nam. The result of this study are as follows: Image factor of the stimulus was composed of 5 different components (visibility, gracefulness, attractiveness, cuteness, womanly). Especially, Neutral color combination independently influenced the every components. In regarding the effect of interaction between each variable, the combination of dot pattern on background of color area ratio, dot pattern size on the combination had cuteness, womanly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.