• 제목/요약/키워드: color model

검색결과 1,695건 처리시간 0.031초

모니터에서 감마변화에 따른 색재현 특성 (Characteristics of Color Reproduction using Gamma Variation on CRT Display)

  • 이성철;차재영;김재해;구철회
    • 한국인쇄학회지
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    • 제23권2호
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    • pp.45-58
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    • 2005
  • The propose of this study investigated the reproduction of color image displayed on a CRT monitor, for a range of different values of monitor gamma. We have used the GOG(gain-offset-gamma) model of the behavior of the CRT. Color difference have been computed in a color space, based on the CIELAB color appearance model. The 133 patch defined linearly color sample and 24 patch defined printing color target were used, and were subjected to the influence of nine different gamma value. The result show that neutral color is increasing the decrease range of luminance black color than white color. These results are of concern in the context of the "correct" display of color reproduction.

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피치 기반 사운드-컬러이미지 변환에 관한 기초연구 (A Basic Study on the Pitch-based Sound into Color Image Conversion)

  • 강건우;김성일
    • 감성과학
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    • 제15권2호
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    • pp.231-238
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    • 2012
  • 본 연구는 하나의 감각으로 인해 다른 영역의 감각을 불러일으키는 공감각 현상을 기초로 하여 사운드에서 컬러이미지를 유추하여 생성하는 응용 시스템의 구현을 최종 목표로 한다. 이를 위해 사운드의 특징정보인 기본주파수(F0, Fundamental Frequency)에서 음계(Scale) 및 옥타브(Octave) 성분을 추출한 후, HSI 컬러모델인 색상(Hue), 명도(Intensity) 성분에 각각 매핑한다. 본 논문에서 채도(saturation)값은 고정된 값을 사용한다. 이를 다시 RGB 컬러모델로 변환한 후 최종 BMP 포맷으로 컬러 이미지를 출력한다. 본 연구에서 제시한 사운드-컬러이미지 변환 방법을 토대로 기본 변환 시스템을 구현해 본 결과, 기본주파수에서 추출된 음계 및 옥타브 성분의 변화에 따라 색상 및 명도가 상이한 다양한 컬러가 나오는 것을 확인할 수 있었다. 또한 하드웨어적 구현을 위해 TMS320C6713 DSP Board에 포팅하여 실험한 결과 제안된 시스템의 시뮬레이션 결과와 동일한 컬러 이미지가 출력됨을 확인하였다.

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An Optimal Combination of Illumination Intensity and Lens Aperture for Color Image Analysis

  • Chang, Y. C.
    • Agricultural and Biosystems Engineering
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    • 제3권1호
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    • pp.35-43
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    • 2002
  • The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

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밝기 변화를 고려한 색상과 채도의 확률 모델에 기반한 조명변화에 간인한 컬러분할 (Color Segmentation robust to Illumination Variations based on Statistical Methods of Hue and Saturation including Brightness)

  • 김치호;유범재;김학배
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권10호
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    • pp.604-614
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    • 2005
  • Color segmentation takes great attentions since a color is an effective and robust visual cue for characterizing one object from other objects. Color segmentation is, however, suffered from color variation induced from irregular illumination changes. This paper proposes a reliable color modeling approach in HSI (Hue-Saturation-Intensity) rotor space considering intensity information by adopting B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to brightness. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in HS (Hue-Saturation) plane. The proposed approach is applied for the segmentation of human skin areas successfully under various illumination conditions.

스캐너를 이용한 직물의 색상검사기 개발 (Development of Color Inspection System of Printed Texture using Scanner)

  • 조지승;정병묵;박무진
    • 한국정밀공학회지
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    • 제20권8호
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    • pp.70-75
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    • 2003
  • It is very important to inspect the color of printed texture in the textile process. The standard colorimetric system used for the recognition of the color in the textile industry. It uses XYZ color system defined by CIE (Commission Internationale de 1Eclairage), but is too expensive. Therefore, in this paper, we propose a color inspection system of the printed texture using a color scanner. Because the scanner uses RGB value for color, it is necessary the mapping from RGB to XYZ. However, the mapping is not simple, and the scanner has even positional deviation because of the geometric characteristics. To transform from RGB to XYZ, we used a NN (neural network) model and also compensated the positional deviation. In real experiments, we could get fairly exact XYZ value from the proposed color inspection system in spite of using a color scanner with large measuring area.

Color Space Based Objects Detection System from Video Sequences

  • Alom, Md. Zahangir;Lee, Hyo Jong
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 추계학술발표대회
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    • pp.347-350
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    • 2011
  • This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

신경망과 적응적 스킨 칼라 모델을 이용한 얼굴 영역 검출 기법 (Human Face Detection from Still Image using Neural Networks and Adaptive Skin Color Model)

  • 손정덕;고한석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 하계종합학술대회 논문집
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    • pp.579-582
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    • 1999
  • In this paper, we propose a human face detection algorithm using adaptive skin color model and neural networks. To attain robustness in the changes of illumination and variability of human skin color, we perform a color segmentation of input image by thresholding adaptively in modified hue-saturation color space (TSV). In order to distinguish faces from other segmented objects, we calculate invariant moments for each face candidate and use the multilayer perceptron neural network of backpropagation algorithm. The simulation results show superior performance for a variety of poses and relatively complex backgrounds, when compared to other existing algorithm.

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Multiple Human Recognition for Networked Camera based Interactive Control in IoT Space

  • Jin, Taeseok
    • 한국산업융합학회 논문집
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    • 제22권1호
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    • pp.39-45
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    • 2019
  • We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

색상 그룹핑과 클러스터링을 이용한 회화 작품의 자동 팔레트 추출 (Automatic Color Palette Extraction for Paintings Using Color Grouping and Clustering)

  • 이익기;이창하;박재화
    • 한국정보과학회논문지:시스템및이론
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    • 제35권7호
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    • pp.340-353
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    • 2008
  • 화풍을 효과적이고 객관적으로 기술하는 한 방법으로 팔레트 추출에 대한 수학적 모델을 제시한다. 이 모델에서는 팔레트를 허용 오차 범위 내에서 회화 작품의 영상을 표현할 수 있는 주요 색상의 집합으로 정의하고 색상 그룹핑과 주요 색상 추출의 두 단계를 거처 팔레트 색상을 추출한다. 색상 그룹핑은 주어진 회화에 대해 적응적으로 색의 분해능을 조절하여 각 회화 작품을 이루는 기초 색상을 추출하며 다음 주요 색상 추출 단계에서 이것과 이것이 차지하는 영역에 대한 정보를 바탕으로 K-Means 클러스터링 알고리즘을 적용하여 팔레트를 얻는다. 실험을 통해 유명 화가의 작품을 대상으로 RGB와 CIE LAB 색상 모델을 사용하여 추출한 팔레트를 3차원 색 공간에 표시하였다. 팔레트 색상의 거리를 사용한 화가 분류 실험과 실사 영상의 색채 변환 실험 통해 이 방법이 화풍 분석과 그래픽 분야에 적용될 수 있음을 확인하였다.

Spectrum-Based Color Reproduction Algorithm for Makeup Simulation of 3D Facial Avatar

  • Jang, In-Su;Kim, Jae Woo;You, Ju-Yeon;Kim, Jin Seo
    • ETRI Journal
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    • 제35권6호
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    • pp.969-979
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    • 2013
  • Various simulation applications for hair, clothing, and makeup of a 3D avatar can provide more useful information to users before they select a hairstyle, clothes, or cosmetics. To enhance their reality, the shapes, textures, and colors of the avatars should be similar to those found in the real world. For a more realistic 3D avatar color reproduction, this paper proposes a spectrum-based color reproduction algorithm and color management process with respect to the implementation of the algorithm. First, a makeup color reproduction model is estimated by analyzing the measured spectral reflectance of the skin samples before and after applying the makeup. To implement the model for a makeup simulation system, the color management process controls all color information of the 3D facial avatar during the 3D scanning, modeling, and rendering stages. During 3D scanning with a multi-camera system, spectrum-based camera calibration and characterization are performed to estimate the spectrum data. During the virtual makeup process, the spectrum data of the 3D facial avatar is modified based on the makeup color reproduction model. Finally, during 3D rendering, the estimated spectrum is converted into RGB data through gamut mapping and display characterization.