• Title/Summary/Keyword: color images

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Eliminating Color Mixing of Projector-Camera System for Fast Radiometric Compensation (컬러 보정의 고속화를 위한 프로젝터-카메라 시스템의 컬러 혼합 성분 제거)

  • Lee, Moon-Hyun;Park, Han-Hoon;Park, Jong-Il
    • Journal of Broadcast Engineering
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    • v.13 no.6
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    • pp.941-950
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    • 2008
  • The quality of projector output image is influenced by the surrounding conditions such as the shape and color of screen, and environmental light. Therefore, techniques that ensure desirable image quality, regardless of such surrounding conditions, have been in demand and are being steadily developed. Among the techniques, radiometric compensation is a representative one. In general, radiometric compensation is achieved by measuring the color of the screen and environmental light based on an analysis of camera image of projector output image and then adjusting the color of projector input image in a pixel-wise manner. This process is not time-consuming for small sizes of images but the speed of the process drops linearly with respect to image size. In large sizes of images, therefore, reducing the time required for performing the process becomes a critical problem. Therefore, this paper proposes a fast radiometric compensation method. The method uses color filters for eliminating the color mixing between projector and camera because the speed of radiometric compensation depends mainly on measuring color mixing between projector and camera. By using color filters, there is no need to measure the color mixing. Through experiments, the proposed method improved the compensation speed by 44 percent while maintaining the projector output image quality. This method is expected to be a key technique for widespread use of projectors for large-scale and high-quality display.

Development of Color Image Processing System based on Spectral Reflectance Ratio (분광반사율에 기반한 색영상처리 시스템 개발)

  • 방상택;오현수;안석출
    • Journal of the Korean Graphic Arts Communication Society
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    • v.18 no.1
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    • pp.25-33
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    • 2000
  • In recent year, many imaging systems have been developed, and it became increasingly important to exchange image data through the computer network. Therefore, it is required to reproduce color image independently on each imaging device. However, even if the image are same, perceived color is not always same under different viewing conditions. On the other hand, even if the image are different, we want to perceive same color under different viewing conditions. Therefore we must know the spectral reflectance information of object. We measured many reflectance human skin can be estimate using only three principal component. For Munsell color patches, five principle components were necessary to estimate the reflectance spectra. For that purpose, we have developed color image acquisition system that is composed of five band filters and CCD camera. Improved spectral reflectance of object is predicted by five band images taken by color image acquisition system and then we take account of camera's noise and component of object image for predicting accurate spectral reflectance of object. In the results, we confirmed that color difference and MSE(Mean Square Error) between measured and predicted spectral reflectance of object decreased into 0.0071 and 7.72 respectively.

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Edge Adaptive Color Interpolation for Ultra-Small HD-Grade CMOS Video Sensor in Camera Phones

  • Jang, Won-Woo;Kim, Joo-Hyun;Yang, Hoon-Gee;Lee, Gi-Dong;Kang, Bong-Soon
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.51-58
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    • 2010
  • This paper proposes an edge adaptive color interpolation for an ultra-small HD-grade complementary metal-oxide semiconductor (CMOS) video sensor in camera phones that can process 720-p/30-fps videos. Recently, proposed methods with great image quality perceptually reconstruct the green component and then estimate the red/blue component using the reconstructed green and neighbor red and blue pixels. However, these methods require the bulky memory line buffers in order to temporally store the reconstructed green components. The edge adaptive color interpolation method uses seven or nine patterns to calculate the six edge directions. At the same time, the threshold values are adaptively adjusted by the sum of the color values of the selected pixels. This method selects the suitable one among the patterns using two flowcharts proposed in this paper, and then interpolates the missing color values. For verification, we calculated the peak-signal-to-noise-ratio (PSNR) in the test images, which were processed by the proposed algorithm, and compared the calculated PSNR of the existing methods. The proposed color interpolation is also fabricated with the 0.18-${\mu}m$ CMOS flash memory process.

Adaptive White Point Extraction based on Dark Channel Prior for Automatic White Balance

  • Jo, Jieun;Im, Jaehyun;Jang, Jinbeum;Yoo, Yoonjong;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.6
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    • pp.383-389
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    • 2016
  • This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

Efficient Method to Detect Color Codes - RHOW Algorithm (효율적 칼라코드 검출법 - 우선법 알고리즘)

  • 권병훈;유현중
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.5 no.1
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    • pp.69-72
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    • 2004
  • Compared to the barcode which is being widely employed to store information on products, the color code may find more various applications because of its favorable appearance and larger possible number of combinations. However, the color values read in practice may suffer from distortions from environments and devices. In this paper, we propose efficient ways to reduce the effect of such distortions and to detect color codes. for which we apply the Right Hand on Wall (RHOW) algorithm originated from the area of the maze search. The color codes used in this paper have high values of Hue and Saturation components and have a circular shape. We first preprocessed the images to detect candidate areas of color codes, and then applied the RHOW algorithm to determine optimal coordinates of rectangles enclosing the areas. As a result, we could obtain accurate coordinates of color codes by using the RHOW algorithm.

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Genetic Programming based Illumination Robust and Non-parametric Multi-colors Detection Model (밝기변화에 강인한 Genetic Programming 기반의 비파라미터 다중 컬러 검출 모델)

  • Kim, Young-Kyun;Kwon, Oh-Sung;Cho, Young-Wan;Seo, Ki-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.6
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    • pp.780-785
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    • 2010
  • This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

Aesthetic-Measure, and Visual Preference of Environmental Colors in Korea Rural Town (농촌마을 환경색채 미도(美度)와 선호도 관계 및 적용성 연구)

  • Lee, Young;Ahn, Tong-Mahn
    • Journal of Korean Society of Rural Planning
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    • v.16 no.2
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    • pp.11-19
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    • 2010
  • Pro-environmental life styles, foundations of a collective civilization and preservation of our tradition at rural communities hold a great public profit value, of which importance has been strongly emphasized during last decade. Here, the environmental color is one of the most influential elements that determine the image of the rural landscape. Whenever an alternative color element is introduced to rural town, it is very important to examine its effect on the existing environmental color. Typically, a preference-surveying method has been used to evaluate the suitability of such environmental color balance. However, we note that the reliability of this method is limited by the subjectivity of a respondent. And thus, it is highly desirable to develop a more objective method. We propose a feasibility study for using an aesthetic-measure to evaluate the environmental color of a rural town. In this work, we looked into the validity of our approach by comparing its result with that of the preference-based-method as a way to determine the environmental color. Our study is based on 20 photo images from Ansung-city Yangsung-myeon Donghang 2ri Kyo-dong town in Kyongki Province.

Hair Design Study Embodying the Symbolic Image of Water

  • Jin Hyun Park;Hye Rroon Jang
    • International Journal of Advanced Culture Technology
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    • v.12 no.4
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    • pp.27-36
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    • 2024
  • In contemporary society, the growing emphasis on appearance as a key factor in shaping one's external image has become a criterion for evaluating individuals and plays a significant role in influencing interpersonal relationships.The quickest way to alter one's appearance is by changing one's Hair style. This not only reflects an individual's sense of beauty through the medium of hair but also conveys the cultural elements valued by the society to which the individual belongs.Since color serves as a catalyst in our lives and enables us to distinguish between objects, the images evoked by color can elicit various emotional responses in individuals. Therefore, we develop a functional color plan based on scientific research. Recently, as the demands for functionality, culture, and aesthetics have evolved beyond the mere application of color in various fields, there is an increasing need for objective and rational data regarding the effects of color. As the use of color has expanded across different domains, color planning has become more sophisticated, incorporating complex elements such as image association, symbolism, functionality, safety colors, and restricted colors.It has long been recognized as essential for all living organisms, including humans. Water possesses numerous physical properties, and its transparency gives rise to a phenomenon known as refraction. The refractive properties of water distort the shapes of objects viewed through it and alter the direction and appearance of light passing through. In this study, we aim to convey the visual and sensory experience of water through hair dyeing and hairstyling, drawing inspiration from its symbolism and material properties.

Color Analyses on Digital Photos Using Machine Learning and KSCA - Focusing on Korean Natural Daytime/nighttime Scenery - (머신러닝과 KSCA를 활용한 디지털 사진의 색 분석 -한국 자연 풍경 낮과 밤 사진을 중심으로-)

  • Gwon, Huieun;KOO, Ja Joon
    • 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.

Efficient Color Correction for 3D rendered images using Adobe camera raw (Adobe Camera Raw를 이용한 효과적인 3D 렌더 이미지 보정)

  • Yoon, Youngdoo;Choi, Eun-Young
    • Cartoon and Animation Studies
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    • s.33
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    • pp.425-447
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    • 2013
  • Due to the popularity of digital cameras, there are lots of studies based on ISP(Image Signal Process) and the image correction applications which can easily use for users are being developed. Specially AWB(Automatic White Balance) and Auto exposure are the most interesting fields in ISP function, and they are well used to increase the quality of image. Principles of camera and lighting in 3D program are made based on real camera and lighting. But the functions of automatic exposure and AWB Which are operated in real camera don't work in 3D program. The color correction of images need expertise, it is true that the functions of compositing program are more difficult than the general correction way of digital image. Specially in case of students who studies animation at the university, they make the animation with compositing and rendering without color correction. Thus this research proposed 3D image making process which make to increase the quality of animation, even though the layman can easily correct the color using functions of digital image correction.