• Title/Summary/Keyword: Color pixels

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Comparisons of Color Spaces for Shadow Elimination (그림자 제거를 위한 색상 공간의 비교)

  • Lee, Gwang-Gook;Uzair, Muhammad;Yoon, Ja-Young;Kim, Jae-Jun;Kim, Whoi-Yul
    • 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.

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Color image segmentation based on clustering using color space distance and neighborhood relation among pixels (픽셀간의 칼라공간에서의 거리와 이웃관계를 고려하는 클러스터링을 통한 칼라영상 분할)

  • 김황수;이화정
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.532-534
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    • 1998
  • 본 논문에서는 칼라공간상의 거리와 이웃정보를 이용한 클러스터링을 통한 칼라영상 분할 방법을 제안한다. 영상의 픽셀들을 이웃관계를 유지하여 칼라공간으로 매핑한다. 칼라공간상에서 이웃하는 픽셀들을 클러스터링하여 영상의 세그먼트들을 찾는다. 클러스터링 방법으로서 인력을 모방하는 클러스터링(gravitational clustering)을 사용하였다. 이 방법으로 클러스터의 중심값과 클러스터 수를 미리 정해주지 않아도 자동적으로 결정할 수 있는 장점이 있다. gravitational 클러스터링에서 찾은 클러스터 수를 가지고 다른 클러스터링 방법에 입력으로 주어 결과를 비교해 본다. 본 논문에서는 이웃관계를 따라 클러스터링하는 것이 정확한 경계선을 찾는데 효과적임을 보여준다.

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A novel LED display architecture using 4 color sub-pixel rendering (4 컬러 서브픽셀 렌더링 적용 고해상도 LED Display)

  • kim, Dae-Sik;Shigeta, Tetsuya;Im, Sang-Kyun;Lee, Ho-Sup
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2015.11a
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    • pp.182-184
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    • 2015
  • We have developed a novel LED display architecture with RGGB 4sub-pixels rendering. LED light control filter algorithm is proposed in order to reduce color fringes by sub-pixel rendering which is a method of perceptual enhancement. The results show that it has 2 times higher perceptual resolution without artifacts.

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The Color Cross-Correlogram for the Robust Image Retrieval in the Size Change of Regions (영역의 크기 변화에 강인한 영상 검색을 위한 칼라 크로스-코렐로그램)

  • An, Myoung-Seok;Cho, Seok-Je
    • The KIPS Transactions:PartB
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    • v.9B no.6
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    • pp.753-758
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    • 2002
  • This paper proposes the color Cross-correlogram and its extraction method for efficient image retrieval. Color cross-correlogram represents the probability that different colors are existed at any two pixels whose distance is fixed in an image. Color cross-correlogram doesn't have the information about the region size that has a color, so color cross-correlogram can have good performance in retrieving images that have different size color regions. The experiments say that we can get the good retrieval results in the images that have various size color regions, and get the better retrieval results when using color cross-correlogram than those of retrieval using color correlogram.

Machine's Determination of Main Color and Imbalance in a Drawing for Art Psychotherapy (그림진단을 위한 주제색 및 불균형 판단의 자동화)

  • Bae Jun;Kim Jae Min;Kim Seong-in
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.119-129
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    • 2006
  • Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye's color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.

Image Retrieval Using Histogram Refinement Based on Local Color Difference (지역 색차 기반의 히스토그램 정교화에 의한 영상 검색)

  • Kim, Min-KI
    • Journal of Korea Multimedia Society
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    • v.18 no.12
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    • pp.1453-1461
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    • 2015
  • Since digital images and videos are rapidly increasing in the internet with the spread of mobile computers and smartphones, research on image retrieval has gained tremendous momentum. Color, shape, and texture are major features used in image retrieval. Especially, color information has been widely used in image retrieval, because it is robust in translation, rotation, and a small change of camera view. This paper proposes a new method for histogram refinement based on local color difference. Firstly, the proposed method converts a RGB color image into a HSV color image. Secondly, it reduces the size of color space from 2563 to 32. It classifies pixels in the 32-color image into three groups according to the color difference between a central pixel and its neighbors in a 3x3 local region. Finally, it makes a color difference vector(CDV) representing three refined color histograms, then image retrieval is performed by the CDV matching. The experimental results using public image database show that the proposed method has higher retrieval accuracy than other conventional ones. They also show that the proposed method can be effectively applied to search low resolution images such as thumbnail images.

Gamut Compression and Extension Algorithms Based on Observer Experimental Data

  • Kang, Byoung-Ho;Morovic, Jan;Luo, M. Ronnier;Cho, Maeng-Sub
    • ETRI Journal
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    • v.25 no.3
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    • pp.156-170
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    • 2003
  • Gamut compression algorithms have traditionally been defined functionally and then tested with deductive methods, e.g., psychophysical experiments. Our study offers an alternative, an inductive method, in which observers judge image colors to represent the original images more accurately. We developed a computer-controlled interactive tool that modifies the color appearance of pictorial images displayed on a monitor. In experiments, observers used the tool to alter color pixels according to the region of color space to which they belonged. We created three different gamut compression algorithms based on the observer experimental data. Observer groups evaluated the performance of the newly-developed algorithms, existing gamut compression algorithms, and an image based on the average observers' results from experiments in this study. The study of gamut extension is unlike the study of gamut compression in that it mainly deals with the degree of image pleasantness as judged by observers. The results of the gamut extension experiments in this study not only make available worthwhile data but also suggest a methodology for using the observer experimental tool for future gamut extension research.

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Color Image Segmentation Using Characteristics of Superpixels (슈퍼픽셀특성을 이용한 칼라영상분할)

  • Lee, Jeong-Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.649-651
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    • 2012
  • In this paper, a method of segmenting color image using characteristics of superpixels is proposed. A superpixel is consist of several pixels with same features such as luminance, color, textures etc. The superpixel can be used for image processing and analysis with large scale image to get high speed processing. A color image can be transformed to $La^*b^*$ feature space having good characteristics, and the superpixels are grouped by clustering and gradient-based algorithm.

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Colorization-based Coding By Using Watershed Segmentation For Optimization

  • Wang, Ping;Lee, Byung-Gook
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.40-42
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    • 2012
  • Colorization is a method using computer to add color to a black and white image automatically. The input is a grayscale image and some representative pixels (RPs). The RPs contain the color information for the image, and it indicates each region's color information. Colorization-based coding is a novel way for lossy image compression, it decodes a color image to get grayscale image and extracts RPs from the image. Because RPs decides the region's color and we also want small data size for image compression, form this viewpoint the paper proposes a way to get better and fewer RPs based on watershed segmentation. According to the segmentation result we also improve the original chrominance blending colorization method to save decode time and get better reconstruct image.

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Skin Color Detection Based on Partial Connections of MLP (부분연결을 사용한 MLP에 기반을 둔 피부색 검출)

  • Kim, Sung-Hoon;Lee, Hyon-Soo
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.681-682
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    • 2008
  • This paper propose skin color detection that uses MLP(Multi Layer Perceptron) and multiple color models. The proposed method reduces weight of MLP by partial connection between input layer and hidden layer based on color models, and the using color models are RGB model and YCbCr model. The experimental result for proposed method showed 94% classification rate of skin and non-skin pixels with 32% decrease in the number of weight compare to general MLP on the average.

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