• Title/Summary/Keyword: Color pixels

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An EM Algorithm-Based Approach for Imputation of Pixel Values in Color Image (색조영상에서 랜덤결측화소값 대체를 위한 EM 알고리즘 기반 기법)

  • Kim, Seung-Gu
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.305-315
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    • 2010
  • In this paper, a frequentistic approach to impute the values of R, G, B-components in random missing pixels of color image is provided. Under assumption that the given image is a realization of Gaussian Markov random field, its model is designed such that each neighbor pixel values for a given pixel follows (independently) the normal distribution with covariance matrix scaled by an evaluates of the similarity between two pixel values, so that the imputation is not to be affected by the neighbors with different color. An approximate EM-based algorithm maximizing the underlying likelihood is implemented to estimate the parameters and to impute the missing pixel values. Some experiments are presented to show its effectiveness through performance comparison with a popular interpolation method.

Applicability of Color Corescanner to the Analysis and Data-base of Drill Cores (시추코어 분석 및 데이터베이스화를 위한 칼라 코어스캐너의 응용)

  • ;Ghodrat Rafat
    • Proceedings of the Korean Geotechical Society Conference
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    • 2001.03a
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    • pp.249-256
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    • 2001
  • Optical Color Corescanner firstly developed by DMT-GeoTec, Germany and further upgraded through the Korea-Germany joint project is capable of duplicating the core surfaces. The tool uses a digital CCD line camera. As the core is rotated by an electric motor, the camera scans the uppermost line, everytime with a circumferential increment of up to 0.05mm(20pixels/mm) and hence a complete 360$^{\circ}$ unwrapped image(core image) is produced. This paper illustrated diverse research benefits of such core images from several test sites in our country. All scanned images could be stored as a data-base one and easily used with software facilities \circled1 to evaluate a percental distribution of mineral components or grain size etc. not only for the rock classification but also for e.g. the assessment of building stones, \circled2 to study potential reservoirs as a hydrocarbon indicator using ultraviolet fluorescence reflection from cores, \circled3 to facilitate the qualitative and quantitative analysis of fractures, \circled4 to evaluate the fractures and thin bedded reservoirs using spectral color responses. Based on abundant scanning experiments, it would seem that this imaging work should lead to reflecting the future trend in underground survey toward a more comprehensive understanding of the properties and behaviors of in situ rocks.

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Automatic Speechreading Feature Detection Using Color Information (색상 정보를 이용한 자동 독화 특징 추출)

  • Lee, Kyong-Ho;Yang, Ryong;Rhee, Sang-Burm
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.107-115
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    • 2008
  • Face feature detection plays an important role in application such as automatic speechreading, human computer interface, face recognition, and face image database management. We proposed a automatic speechreading feature detection algorithm for color image using color information. Face feature pixels is represented for various value because of the luminance and chrominance in various color space. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, inner boundary of lips and the outer line of the tooth is detected and show very encouraging result.

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Estimating illuminant color using the light locus for camera and highlight on the image (카메라의 조명궤적과 광휘점을 이용한 조명색 추정)

  • Park, Du-Sik;Kim, Chang-Yeong;Seo, Yang-Seock
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.10
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    • pp.94-102
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    • 1999
  • In this paper, an algorithm for estimating the scene-illuminant color directly from an image is proposed. To determine the scene-illuminant color in the image. the intersection point between the light locus of camera (CCD) reponses and an approximated lines for the cluster of pixels in a highlight area on chromaticity coordinates is used. By using the predetermined characteristics of the used camera for some illuminants, this algorithm allows us to obtain more accurate estimation of the scene-illuminatnt color from a captured image than that the previous methods provide.

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The Discharge Control Scheme of Plasma Display Device (플라즈마 디스플레이의 방전제어 기술)

  • 염정덕
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2000.11a
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    • pp.30-34
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    • 2000
  • This study minimized the address pulse width for plasma display by analysis of address discharge condition for high speed driving using the ADS driving scheme. As a result, addressing pulse width of 1$mutextrm{s}$ has been realized and luminance of 560cd/$m^2$ can be obtained from the area of 256X160 pixels. And a new AWD scheme is proposed. We accomplished 9.1-inch-diagonal color image with the scan timing of HDTV class PDP, display duty 96.8%.

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A Graphics Accelerator for Hidden Surface Removal and Color Shading (가려진면 제거와 색도 계산을 위한 그래픽스 가속기)

  • 방경익;배성옥;경종민
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.28A no.5
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    • pp.398-406
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    • 1991
  • This paper presents a graphics accelerator for fast image generation. The accelarator has three major functional blocks: linear interpolator, multipliers and Edgee Painting Tree. Linear interpolator with coupled binary tree structure interpolates functional values of two end points. Two multipliers compute input values of interpolator in parallel. Mask pattern which removes out invalid data is generated by Edge Painting Tree. The proposed architecture in this paper is responsible for 64 pixels and can process about 5,900 10x10polygons per second.

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Distance Measurement Using the Kinect Sensor with Neuro-image Processing

  • Sharma, Kajal
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.6
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    • pp.379-383
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    • 2015
  • This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

Classifying Color Codes Via k-Mean Clustering and L*a*b* Color Model (k-평균 클러스터링과 L*a*b* 칼라 모델에 의한 칼라코드 분류)

  • Yoo, Hyeon-Joong
    • The Journal of the Korea Contents Association
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    • v.7 no.2
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    • pp.109-116
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    • 2007
  • To reduce the effect of color distortions on reading colors, it is more desirable to statistically process as many pixels in the individual color region as possible. This process may require segmentation, which usually requires edge detection. However, edges in color codes can be disconnected due to various distortions such as dark current, color cross, zipper effect, shade and reflection, to name a few. Edge linking is also a difficult process. In this paper, k-means clustering was performed on the images where edge detectors failed segmentation. Experiments were conducted on 311 images taken in different environments with different cameras. The primary and secondary colors were randomly selected for each color code region. While segmentation rate by edge detectors was 89.4%, the proposed method increased it to 99.4%. Color recognition was performed based on hue, a*, and b* components, with the accuracy of 100% for the successfully segmented cases.

Color Image Segmentation based on Clustering using Color Space Distance and Neighborhood Relation Among Pixels (픽셀간의 칼라공간에서의 거리와 이웃관계를 고려하는 클러스터링을 통한 칼라영상 분할)

  • Lee, Hwa-Jeong;Kim, Hwang-Su
    • Journal of KIISE:Software and Applications
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    • v.27 no.10
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    • pp.1038-1045
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    • 2000
  • 본 논문에서는 칼라공간상의 거리와 이웃정보를 이용한 클러스터링을 통한 칼라영상 분할 방법을 제안한다. 칼라영상의 한 픽셀은 칼라정보(R.G.B)와 위치정보(x.y)를 가진다. 대개의 칼라공간에서의 클러스터링방법은 픽셀을 (R,G,B)공간으로 변환후 (R,G,B)공간상의 분포만을 이용하지만 여기서는(R,G,B)와 (x.y)모두를 사용하여 클러스터링함으로 영상의 세그먼트들을 찾는다. 클러스터링 방법으로서 인력을 모방하는 중력 클러스터링(gravitational clustering)을 사용하였다. 이 방법은 클러스터의 중심값과 클러스터 수를 미리 정해주지 않아도 자동적으로 결정할 수 있는 장점이 있다. 중력 클러스터링에서 찾은 클러스터 수를 가지고 다른 클러스터링 방법(K-means)에 입력으로 주어 결과를 비교해 본다. 본 논문에서는 이웃관계를 따라 클러스터링하는 것이 정확한 경계선을 찾는데 효과적임을 보여준다.

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A Design of a Tile-Based Rasterizer Using Varying Interpolator by Pixel Block Unit (Pixel Block 단위 Varying Interpolator를 적용한 타일기반 Rasterizer 설계)

  • Kim, Chi-Yong
    • Journal of IKEEE
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    • v.18 no.3
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    • pp.403-408
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    • 2014
  • In this paper, we propose a rasterizer architecture using varying interpolator which process several pixels at a time. Proposed rasterizer is able to handle 16 pixel at a time and output the color of up to 64. It can reduce the redundancy of calculation by configuring a matrix transformation and matrix calculation for rasterization, and it can enhance the speed of rasterizer by increasing the reusability. As a result, proposed rasterizer has improve 11% in color interpolation, 17% in the processing speed of the rasterizer by comparing with conventional research.