• Title/Summary/Keyword: 색상대비

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Study on the Minimum Recursive Reflection Performance according to the Color of Road Surface (노면표시 색상에 따른 최소재귀반사성능 연구)

  • Han, Eum;Kang, Jong Ho;Kim, Cheong Ho;Park, Sungho;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.37-48
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    • 2020
  • Eight colors prescribed by the Enforcement Rules of the Road Traffic Act and the group standard were tested to secure the minimum recursive reflectance performance standards when drying and wetting. The results were calculated to be 260.8 (mcd/㎡·lux) when drying white and 154.6 (mcd/㎡·lux) when wet. Yellow was 67% compared to the white reflective performance when drying. Wet poetry was 79 % and 59 %, respectively. In the case of blue, it was 64% in the case of white versus 72% in the case of white. Wet poetry was 63 % and 72 %, respectively. The range of changes in reflective performance during wetting was higher than when drying, and the absence of glass grains was similar to the previous results. The new colors also have a standard value of more than 50% compared to the white color in red, orange, pink, light green, and green. Based on this, it was estimated that the minimum reflective performance criteria according to the color of the road markings would form the basis for the enforcement rules of the Road Traffic Act.

Analysis of Color Error and Distortion Pattern in Underwater images (수중 영상의 색상 오차 및 왜곡 패턴 분석)

  • Jeong Yeop Kim
    • Journal of Platform Technology
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    • v.12 no.3
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    • pp.16-26
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    • 2024
  • Videos shot underwater are known to have significant color distortion. Typical causes are backscattering by floating objects and attenuation of red colors in proportion to the depth of the water. In this paper, we aim to analyze color correction performance and color distortion patterns for images taken underwater. Backscattering and attenuation caused by suspended matter will be discussed in the next study. In this study, based on the DeepSeeColor model proposed by Jamieson et al., we verify color correction performance and analyze the pattern of color distortion according to changes in water depth. The input images were taken in the US Virgin Islands by Jamieson et al., and out of 1,190 images, 330 images including color charts were used. Color correction performance was expressed as angular error using the input image and the correction image using the DeepSeeColor model. Jamieson et al. calculated the angular error using only black and white patches among the color charts, so they were unable to provide an accurate analysis of overall color distortion. In this paper, the color correction error was calculated targeting the entire color chart patch, so an appropriate degree of color distortion can be suggested. Since the input image of the DeepSeeColor model has a depth of 1 to 8, color distortion patterns according to depth changes can be analyzed. In general, the deeper the depth, the greater the attenuation of red colors. Color distortion due to depth changes was modeled in the form of scale and offset movement to predict distortion due to depth changes. As the depth increases, the scale for color correction increases and the offset decreases. The color correction performance using the proposed method was improved by 41.5% compared to the conventional method.

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FRIP Stystem For Region-based Image Retrieval (영역기반 검색환경을 위한 FRIP 시스템)

  • 고병철;변혜란
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.499-501
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    • 2000
  • 본 논문에서는 영역기반 검색환경을 제공하는 FRIP(Finding Region in the Pictures) 시스템을 소개한다. FRIP 시스템은 영역 기반 검색환경을 제공하기 위해서, 우선적으로 영상을 분할하고, 각 분할된 영역으로부터 색상, 질감, 크기, 모양, 위치 정보와 같은 최적의 특징 벡터들을 추출하여 색인화시킨다. 그런 뒤에, 사용자가 검색하고자 하는 영역과 검색 영상 수 k를 입력하면, 유사성 측정 식에 의해 가장 유사한 k만큼의 영상을 우선 순위 형태로 사용자에 보여주게 된다. 본 시스템에서는 영상을 분할하기 위해서 기본적인 RGB 색상계를 확장(Scaling 및 이동(Shifting) 알고리즘을 통해 영상의 대비 정도가 향상된 새로운 색상계로 변환시키고, 원형 필터를 설계하여, 영역 안에 포함된 의미 없는 작은 영역을 제거하도록 하였다. 그리고 이렇게 분할된 각 영역들로부터, 본 시스템에서 제안하는 모양 기술자인 MRS(Modified Radius-based Signature)를 포함하여 5가지의 최적의 특징 벡터들을 전처리 단계에서 데이터베이스에 색인으로 저장하고 유사성 측정을 위한 수치로 사용하였다.

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Fast Contrast Enhancement of Noisy Low-Light Video (잡음이 있는 저조도 동영상의 고속 시인성 개선)

  • Heo, Minhyeok;Lim, Jaemoon;Lee, Chulwoo;Park, Taegon;Choi, Jinhyeok;Kim, Chang-Su
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2015.11a
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    • pp.159-160
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    • 2015
  • 본 논문에서는 잡음이 있는 저조도 동영상의 고속 시인성 개선 기법을 제안한다. 먼저, 영상에서 고속 추출한 광도를 기반으로 입력 영상을 저조도 영역과 고조도 영역으로 구분한 뒤, 각 영역의 특징을 반영한 전달 함수의 독립적인 생성 및 적용을 통해 영상의 밝기를 개선한다. 다음으로 동영상의 풍부한 시공간적 정보 활용 극대화를통해 효율적으로 영상의 잡음을 제거한다. 마지막으로 영상의 색상 분포 분석을 통해 매핑 함수를 생성하고, 이를 적용하여 색상 치우침 문제가 있는 저조도 영상의 색상을 효과적으로 복원한다. 실험을 통하여 제안 기법이 기존 기법 대비 우수한 시인성 개선 및 속도 개선 결과를 보임을 확인한다.

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The Impact of Color on the Glove Pitcher Hitting a Batter Concentration (투수의 글러브 색상이 타자의 타격 집중도에 미치는 영향)

  • Kim, HyunBin;Kim, ByoungJun
    • Journal of Digital Convergence
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    • v.15 no.3
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    • pp.405-411
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    • 2017
  • The purpose of this study was to identify the color that you want the pitcher glove hit impact on the intensity of the other. The color of the glove pitcher was set to black, orange, beige three kinds analyzed the concentration of the batter accordingly. Subjects of this study were 15 people targeting high school baseball players in Daejeon, through a pre- test and vision test color blind players were selected with no visual problems. After the blow of the experiment was used to color the glove Nideffer is modified to fit and complement the six subscales B-TAIS. As a result, when wearing a colored glove that contrasts with the color of the ball, the batter's concentration was increased. Hopefully, research will take place using the ball skill and equipment of various pitchers.

Object-based Image Classification by Integrating Multiple Classes in Hue Channel Images (Hue 채널 영상의 다중 클래스 결합을 이용한 객체 기반 영상 분류)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.2011-2025
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    • 2021
  • In high-resolution satellite image classification, when the color values of pixels belonging to one class are different, such as buildings with various colors, it is difficult to determine the color information representing the class. In this paper, to solve the problem of determining the representative color information of a class, we propose a method to divide the color channel of HSV (Hue Saturation Value) and perform object-based classification. To this end, after transforming the input image of the RGB color space into the components of the HSV color space, the Hue component is divided into subchannels at regular intervals. The minimum distance-based image classification is performed for each hue subchannel, and the classification result is combined with the image segmentation result. As a result of applying the proposed method to KOMPSAT-3A imagery, the overall accuracy was 84.97% and the kappa coefficient was 77.56%, and the classification accuracy was improved by more than 10% compared to a commercial software.

Reduction of Color Distortion by Estimating Dominant Chromaticity in Multi-Scaled Retinex (다중 Retinex 알고리즘에서 주색도 추정을 이용한 색상 왜곡 보정)

  • Jang, In-Su;Park, Kee-Hyon;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.3
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    • pp.52-59
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    • 2009
  • In general, methods based on histogram or a correction of gamma curve are usually utilized to enhance the contrast of captured image in the dark scene. These methods are efficient to enhance the contrast globally, however, they locally induced the low quality of image. Recently, to resolve the problem, the multi-scaled refiner algorithm improving the contrast with locally averaged lightness is proposed. However, estimating the locally averaged lightness, if there is the object with a high saturated color, the color distortion might be induced by the color of object. Thus, in this paper, the dominant chromaticity of image is estimated to correct the locally averaged lightness in multi-scaled retinex algorithm. Because the average chromaticity of image includes the chromaticity of illumination, the dominant chromaticity is estimated with dividing the average chromaticity of image by the estimated chromaticity of illumination from highlight region. In addition, to improve the lower chroma by multi-scaled retinex algorithm generally, the chroma was compensated preserving the hue in the CIELAB color space.

Pointillistic Rendering Based on The Juxtaposition of Colors (보색 병치혼합에 기반한 점묘화 렌더링)

  • Seo, Sang-Hyun;Yoon, Kyung-Hyun
    • 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.

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Color Saturation Improvement using the Maximum Color Difference Table (최대색차신호 표를 이용한 컬러 채도 향상)

  • Kim, Sun-Jung;Hong, Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.16 no.2
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    • pp.119-130
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    • 2013
  • In this paper, we propose a new color image enhancement method to improve the color saturation as well as luminance contrast in the YCbCr color space. The proposed method uses the maximum color difference table to compensate the perceived saturation changes due to luminance contrast changes. To improve the color saturation, the method first calculates the weighting factor by using the maximum color difference table and then multiplies the weighting factor to the input color difference signals. In this step, it maps color difference signals to proper color region to prevent the color distortion by considering the correlation of color saturations depending on the luminance and hue. The experimental results show that our method effectively improves color saturation compared to the conventional methods.

The Effect of the Contrast Color Coordination of Clothing and Makeup on Image Formation (의복과 메이크업의 대비색상 코디네이션이 이미지에 미치는 영향)

  • Jeong, Su-Jin
    • Journal of Fashion Business
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    • v.12 no.1
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    • pp.30-44
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    • 2008
  • The purpose of this study is to investigate the effect of eyeshadow color(brown, purple), lipstick color(red, red purple, and yellow red), and lipstick tone(vivid, light, dull, and dark), clothing tone(vivid, light, dull, and dark) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 64 color pictures manipulated with the combination of eyeshadow color, lipstick color, lipstick tone, and clothing tone using computer simulation. The subjects were 384 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 4 different components (attractiveness, visibility, gracefulness, and tenderness). In the 4 image components, eyeshadow color and clothing tone showed independent effect. Lipstick tone influenced independently on the visibility and tenderness. In the contrast color coordination of clothing and makeup, visibility image by the coordination of lipstick color with lipstick tone, lipstick color with clothing tone or lipstick tone with clothing tone, gracefulness image by the coordination of eyeshadow color with lipstick color, tenderness image can be produced by the coordination of eyeshadow color with lipstick color, eyeshadow color with lipstick tone or eyeshadow color with clothing tone.