• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.131-133
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• 2016

본 논문은 연속적인 비디오 시퀀스에서 움직이는 객체의 영역을 효율적으로 분할하기 위하여 커널 기반 객체 추적과 Grab-Cut 알고리즘을 결합한 비디오 영역 분할 방법을 제안한다. 제안 방법에서는 추적 목표 객체의 초기 위치를 사각영역으로 선택하면, 사각의 외부 영역을 배경색상으로 인지하고, 배경 색상을 고려한 목표 객체의 주요 색상을 분석한다. 이를 기반으로 커널기반 객체 추적 기법을 적용하여 빠르게 객체의 영역을 추출한다. 추적한 각 객체의 영역에서 중앙 객체 영역과 배경 영역의 색 정보를 초기값으로 하여 Grab-Cut 알고리즘을 수행하고 사각형 형태가 아닌 객체의 실루엣 최적화된 영역으로 분할한다. 제안 방법을 스포츠 방송, 광고, 영화 등의 특수 효과로 활용되고 있는 stromotion 영상 생성에 적용하기 위하여 프레임별 추출된 객체의 영상을 새로운 프레임 영상에 합성하는 작업을 수행하여, 초당 10 프레임의 처리 속도에서 원하는 스트로모션 효과 영상을 생성하였다.

• The Journal of Korean Academy of Prosthodontics
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• v.16 no.1
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• pp.38-44
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• 1978

Color is an important factor in dental esthetics. Application of natural tooth color will not fail to produce pleasing results. But a standardized method of shade matching has not been adopted. If we are to overcome the color matching problem in dentistry, an understanding of the nature of color and light is essential. The purpose of this study was to compare the effects of different light sources and different background colors on the ability of observers to correctly match shades of artifical teeth. And observation was made to determine if the time spent in making a shade match was a factor in the correctness of the response. A test method was devised and 50 individuals made observations which were recorded and analyzed. $X^2$-test gave results indicating that the time factor had no effect on the response made. An analysis of variance showed the following effects significant at the five percent level; (1) light source (2) background color (3) subject. The following conclusions can be drawn from this study; (1) The time spent in making shade selection is not a factor in the correctness of the selections. (2) The light source used is an important factor in matching tooth shade; and there is no significant difference between the light sources in shade matching. (3) Under the conditions of this study, the greatest accuracy in shade matching was obtained on the brown background.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.785-794
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• 2021

This study investigated the current status of the design and direction of improvement of the sign system of urban railway stations in the Seoul metropolitan area to see how difficult it is for users to use. As a research method, first, a theoretical study on the literature of the urban railway sign system, second, a survey on the current status of the sign design of the Gimpo Goldline in the Seoul metropolitan area, and third, a survey on the actual use of the sign and problems was conducted. As a result of the current status survey, the location sign is in central alignment with the font of the guide sign, and the guidance sign is in front/back alignment according to the location of the entrance and exit. The background of the font is white and the text is dark black to make it look good to the user. On the other hand, guidance sign is written in white color and background color is gray color. Currently, the Gimpo Urban Railway Guidance Sign System is newly produced and installed, but there is a lack of user design and needs design maintenance that can clearly deliver information to users.

• Analytical Science and Technology
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• v.31 no.5
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• pp.195-200
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• 2018

Researchers have used the visual criteria to compare the effectiveness of fingerprint enhancement techniques. However, since the visual criteria is subjective, bias can occur. Therefore, many researchers have tried to make the criteria objective using the contrast index (CI). However, there is a constraint that the CI was only validated on inked fingerprints or color-change fingerprints. In this study, we compared enhancement of fluorescence fingerprints on colored papers using the CI. The CI values differ according to the color of the background, reagent, and light source, even though the same standard fingerprints were used. Through the comparison of values, we could compare the enhancement of fluorescence fingerprints according to these factors. When visual evaluation criteria were used, the same peak score was obtained regardless of the reagent and light source. However, we could get a more detailed score comparison in this study using the CI. Therefore, it is confirmed that for comparison of enhancement of fluorescence fingerprints, the CI can be used as a basis for determining which light source and reagent are appropriate according to the background.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.610-622
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• 2008

Moving object segmentation is an essential technique for various video surveillance applications. The result of moving object segmentation often contains shadow regions caused by the color difference of shadow pixels. Hence, moving object segmentation is usually followed by a shadow elimination process to remove the false detection results. The common assumption adopted in previous works is that, under the illumination variation, the value of chromaticity components are preserved while the value of intensity component is changed. Hence, color transforms which separates luminance component and chromaticity component are usually utilized to remove shadow pixels. In this paper, various color spaces (YCbCr, HSI, normalized rgb, Yxy, Lab, c1c2c3) are examined to find the most appropriate color space for shadow elimination. So far, there have been some research efforts to compare the influence of various color spaces for shadow elimination. However, previous efforts are somewhat insufficient to compare the color distortions under illumination change in diverse color spaces, since they used a specific shadow elimination scheme or different thresholds for different color spaces. In this paper, to relieve the limitations of previous works, (1) the amount of gradients in shadow boundaries drawn to uniform colored regions are examined only for chromaticity components to compare the color distortion under illumination change and (2) the accuracy of background subtraction are analyzed via RoC curves to compare different color spaces without the problem of threshold level selection. Through experiments on real video sequences, YCbCr and normalized rgb color spaces showed good results for shadow elimination among various color spaces used for the experiments.

• Journal of the Korea Computer Graphics Society
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• v.12 no.1
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• pp.9-15
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• 2006

본 논문에서는 점묘화를 생성하기 위한 회화적 렌더링 기법을 제안한다. 신인상파(Neo-Impressionist) 화가 쇠라는 캔버스위의 독립 색채들은 망막위에서 재조직된다는 이론을 바탕으로 점묘화를 제안한다. 이는 색의 병치혼합과 보색대비를 이용해 빛의 가산혼합이 회화작품에 적용될 수 있도록 하기위해 브러시 스트로크로 작은 점을 이용한다. 이러한 점묘화를 표현하기위해서 쇠라의 작품과 동시대의 색이론 분석을 통해 색의 분할과 병치혼합의 이론적 배경을 알아보고 이를 통해 점묘 스트로크의 색상, 모양, 방향등을 결정할 수 있는 알고리즘을 소개한다. 먼저 신인상파의 팔레트 분석을 통해 칼라모델을 설계한다. 그리고 입력영상을 영상분할 기법을 이용해 공간적 구도를 잡고 각 분할 영역의 관계를 고려해 색상을 할당한다. 각 할당된 색은 보색과 함께 정의된다. 각 분할영역은 해당영역에서 표현될 수 있는 색상의 작은 점묘 브러시 스트로크로 렌더링이 된다. 이때 입력영상의 밝기정보를 유지할 수 있도록 점묘 스트로크는 색상이 결정된다. 점묘 스트로크의 방향은 입력영상의 에지방향을 따르도록 보간법을 이용해 계산한다.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1835-1838
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• 2003

Texts in natural images contain significant and detailed informations about the images. Thus, to extract those texts correctly, we suggest a text extraction method using color variance feature. Generally, the texts in images have color variations with the backgrounds. Thus, if we express those variations in 3 dimensional RGB color space, we can emphasize the text regions that can be hard to be captured with a method using intensity variations in the gray-level images. We can even make robust extraction results with the images contaminated by light variations. The color variations are measured by color variance in this paper. First, horizontal and vertical variance images are obtained independently, and we can fine that the text regions have high values of the variances in both directions. Then, the two images are logically ANDed to remove the non-text components with only one directional high variance. We have applied the proposed method to the multiple kinds of the natural images, and we confirmed that the proposed feature can help to find the text regions that can he missed with the following features - intensity variations in the gray-level images and/or color continuity in the color images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.69-78
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• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.

• Journal of Naturopathy
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• v.11 no.2
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• pp.123-135
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• 2022

Background: The study aims to examine what color representation means to artists by investigating various hypotheses about van Gogh's expression of yellow and verifying the reason of his preference of yellow. Purpose: The purpose of this study is to investigate whether yellow expression of Vincent van Gogh is a result of physiological responses of alcoholism, expression feature of mental disorder, or a problem caused by psychological motivation. Methods: In order to verify the research question, we referred to research literatures that analyzed a characteristics of Gogh's works in a various area such as psychology and psychiatry, and Gogh's symptoms and his own skills. Results: The findings suggested that Gogh's yellow preference is related to the psychological factors such as inner motivation, not a xanthopsia which is brought about alcoholism and mental disorder. Conclusions: Gogh's Yellow expression is dominantly influenced by the psychological factors. Thus, it can say that the psychological factors has a great on characteristic of artist's color expression.