• Journal of the Korea Fashion and Costume Design Association
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• v.3 no.2
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• pp.87-106
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• 2001

This study is to measure and evaluate the sensibility image for textile color and pattern design of woman's golfwear. Four-group colors and four patterns classified by a pracical survey on the market are presented. A questionnaire has 14 sensibility related words scaled by 7 point semantic differential method. The practical research is performed for 150 women screened by sensibility test for individual preference analysis based on the ages. Each subject is answered by a face-to-face interview method to improve survey's accuracy. For statistical results there are significant differences in treatment means of sensibility measurements according to the ages. Sensibility image for textile color and pattern design is significantly different according to individual character based on ages. In summary, this paper has proposed the sensibility image scale for textile color and pattern design of women's golfwears to satisfy individual sensibility according to ages. The results of this study can be effectively applied to develop textile color and pattern design based on human sensibility.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.89-97
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• 2015

In this paper, a method of color image segmentation based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) using compactness of superpixels and texture information is presented. The DBSCAN algorithm can generate clusters in large data sets by looking at the local density of data samples, using only two input parameters which called minimum number of data and distance of neighborhood data. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. Each superpixel is consist of pixels with similar features such as luminance, color, textures etc. Superpixels are more efficient than pixels in case of large scale image processing. In this paper, superpixels are generated by SLIC(simple linear iterative clustering) as known popular. Superpixel characteristics are described by compactness, uniformity, boundary precision and recall. The compactness is important features to depict superpixel characteristics. Each superpixel is represented by Lab color spaces, compactness and texture information. DBSCAN clustering method applied to these feature spaces to segment a color image. To evaluate the performance of the proposed method, computer simulation is carried out to several outdoor images. The experimental results show that the proposed algorithm can provide good segmentation results on various images.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.1-6
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• 2014

Emotion recognition is defined as that machines automatically recognize human emotions. Because the human emotions is very subjective, it is impossible to measure objectively. Therefore, the goal of emotion recognition is to obtain a measure that is agreed by as many people as possible. Emotion recognition in a image is implemented as the method that matches human emotions to the various features of the image. In the paper, we propose an emotion recognition system using color features of clothing image based on the Kobayashi's image scale. The proposed system stores colors of image scale into a database. And extracted major colors from a input clothing image are compared with those in the database. The proposed system can obtain three emotions maximally. In order to evaluate the system performance 70 observers are tested. The test results shows that recognized emotions of the proposed system are very similar to the observers emotions.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.304-306
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• 2007

Methods of Object recognition from camera image are to compare features of color. edge or pattern with model in a general way. SIFT(scale-invariant feature transform) has good performance but that has high complexity of computation. Using simple color histogram has low complexity. but low performance. In this paper we represent a model as a color cooccurrence histogram. and we improve performance using pyramid matching. The color cooccurrence histogram keeps track of the number of pairs of certain colored pixels that occur at certain separation distances in image space. The color cooccurrence histogram adds geometric information to the normal color histogram. We suggest object recognition by pyramid matching of color cooccurrence histogram.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.42-50
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• 2015

In the 21st century, university library is changing into a new paradigm. Among others, color image emerges as an important aspect of the library. Up to now, studies on colors of indoor space have been limited on partial and specific spaces. But, this study, using the tool of emotional evaluation, aims to do a comprehensive research on color image of the whole space. This research uses the H University library completed in March 2015. This research is performed in the following procedure. First, previous related researches for the past ten years from 2005 to 2015 is examined, which will help understand the trends in this kind of research, and set up the concrete goal of research. By literature review, color image is established in the environmental psychological aspect. Second, to analyze colors, all the spaces of the library from the entrance lobby are filmed. Filmed images are changed into mosaic, and color palettes are composed, and color values are calculated using the Munsell color system. Third, emotional words are extracted, and emotional evaluation is made. Using the Semantic Differential scale method, emotional differences among subjects are compared, and the validity of the survey data is tested using the statistical program SPSS 18.0. As the outcome of the research shows, the color image and emotion in space are closely related. And, through emotion, it is possible to get color image, and this aspect can be scholastically systemized and developed.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.53-62
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• 2012

Object segmentation is a demanding research area and not a trivial problem of image processing and computer vision. Tremendous segmentation algorithms were addressed on gray-scale (or biomedical) images that rely on numerous image features as well as their strategies. These works in practice cannot apply to natural color images because of their negative effects to color values due to the use of gray-scale gradient information. In this paper, we proposed a new approach for color object segmentation by modifying a geometric active contour model named distance regularized level set evolution (DRLSE). Its speed function will be designed to exploit as much as possible color gradient information of images. Finally, we provide experiments to show performance of our method with respect to its accuracy and time efficiency using various color images.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.217-220
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• 2001

The detection of face in color images is important for many multimedia applications. It is the first step for face recognition and ran be used for classifying specific shots. In this paper describes a new method to detect faces in color images based on the skin color and hair color. In the first step of the processing, regions of the human skin color and head color are extracted and those regions are found by their color information. Then we converted binary scale from the image. Then we are connected regions in a binary image by label. In the next step we are found regions of interesting by their region information and some conditions.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.27-45
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• 2024

The purpose of this study is to analyze the colors in the school libraries and identify the images of adjectives derived from the colors. This study investigated the hue (basic color), value (brightness) and chroma (color intensity) in the school libraries through KSCA program. It analyzed 15 school libraries from elementary schools to high schools. Furthermore, with the aids of I.R.I Adjective Image Scale, the adjective images of the colors could be identified. The results are as follows: In the elementary school libraries, the hue was used in the order of YR (yellow red), N (neutral), and Y (yellow), while in the order of YR (yellow red), N (neutral), and R (red) in the middle school libraries. All the school libraries had medium brightness on average, whereas the colors had a low chroma. As for the adjective images of the colors, the adjective 'gentle' has appeared the most in every school library. The school libraries have similar colors and adjective images for all levels, not presenting any particular differences in the colors of every interior space arrangement.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.281-289
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• 2013

The iCAM06 has been used as an image appearance model for HDR image rendering. The iCAM06 goes through the color space conversions and scale conversions of the several steps to present HDR images. The dynamic range of an HDR image needs to be mapped on the range of output devices, which is called the tone mapping. However, tone compression process of the iCAM06 causes color distortion because of color-clipping and cross-stimulus. Therefore, we proposed that a color correction method in IPT space which compensates the color distortion in tone compression process. Through the experimental results, we conformed that proposed color correction method had better performance than the iCAM06 and enhanced models.

• Journal of the Korea Fashion and Costume Design Association
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• v.12 no.3
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• pp.133-143
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• 2010

The purpose of this study was to investigate the clothing image according to gender, coloration of chromatic and achromatic color, and interval of checked pattern. The experimental materials developed for this study were a set of stimulus and response scales. The stimuli were 16 color pictures, in which the gender(male, female), interval(0.5cm, 1.5cm, 3.5cm, 5.5cm), and coloration(WR: white+red, WY: white+yellow, WB: white+Blue, WP: white+purple) were manipulated. The 7-point scale was used for evaluation of clothing image. Data were obtained from 192 male college students and 192 female college students living in Seoul, Gwangju, Daegu, Jinju, and Changwon on March 2010. For data analysis, ANOVA and Duncan-test were used by using SPSS program. Results of this study were as follows.; Clothing image according to coloration of chromatic and achromatic color, and interval of checked pattern consisted of six dimensions of attractiveness, appeal, activity, freshness, modesty, and cuteness. Gender showed an independent effect on attractiveness, appeal, activity, freshness, and cuteness. Interval showed an independent effect on attractiveness. Coloration showed an independent effect on appeal, activity, freshness, modesty, and cuteness. Also, interaction effects of gender and coloration on freshness and cuteness were found.