• 제목/요약/키워드: Color Image Processing

검색결과 1,055건 처리시간 0.029초

색조 보존을 위한 칼라 색역 매핑 (Hue Preserving Color Gamut Mapping)

  • 성영모;박은홍;임재권
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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    • pp.106-109
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    • 2003
  • This paper presents a hue preserving gamut mapping algorithm for color monitor and printer. The gamuts of monitor and printer are set by the profile of color reproduction media, specified by ICC(International Color Consortium) and provided by vendors, then those gamuts are represented on the CIE xy color space. In case that the color of monitor are located on out-of-gamut of printer, these are clipped on the point of gamut boundary of printer towards a reference white point. On the other hand, colors are in-gamut of printer are unchanged. An image generated by the algorithm keeps a ratio of each pixel of original image. Advantages of the algorithm are easy to implement and fast processing time than other algorithms which involve hue preserving especially in CIELAB color space.

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PC를 이용한 GMS/WEFAX 수신 및 영상처리 시스템 개발(II) - 수신 및 영상처리 소프트 웨어 - (Development of Receiving and Image Processing System of GMS/WEFAX Using PC(II) - Software for Receiving and Image Processing -)

  • 서명석;박경윤
    • 대한원격탐사학회지
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    • 제9권1호
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    • pp.37-49
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    • 1993
  • In this research, the WEF AX and APT(Automatic Picture Transmission) data receiving and image processing software using PC/AT called WADIPS(WEFAX and APT Data Integrated Processing System) Software has been developed. The main functions of WADIPS software are follow : 1) Real time receiving and saving to hard disk of WEFAX and APT data 2) B/W(Black and White) and false color display 3) Image enhancement using histogram stretch and color control 4) 2-4 times zooming 5) Hard copy of data using dithering and patterning 6) Animation 7) File management 8) On line help. WADIPS can be used in the offices or persons need real time meteorological information and education offices to teach the image processing technique and general characteristics of meteorological satellites.

인간 시각의 칼라 활성 가중 왜곡 척도를 이용한 칼라 영상 양자화 (Color image quantization using color activity weighted distortion measure of human vision)

  • 김경만;이응주;박양우;이채수;하영호
    • 전자공학회논문지B
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    • 제33B권4호
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    • pp.101-110
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    • 1996
  • Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. the basic problem is how to display 224 colors with 256 or less colors, called color palette. In this paper, we propose an algorithm to design the 256 or less size color palette by using spatial maskin geffect of HVS and subjective distortion measure weighted by color palette by using spatial masking effect of HVS and subjective distortion measure weighted by color activity in 4*4 local region in any color image. The proposed algorithm consists of octal prequantization and subdivision quantization processing step using the distortion measure and modified Otsu's between class variance maximization method. The experimental results show that the proposed algorithm has higher visual quality and needs less consuming time than conventional algorithms.

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GRADING CUT ROSES BY COLOR IMAGE PROCESSING AND NEURAL NETWORK

  • Bae, Y.H.;Seo, H.S.
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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    • pp.170-177
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    • 2000
  • Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

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Color Enhancement of Low Exposure Images using Histogram Specification and its Application to Color Shift Model-Based Refocusing

  • Lee, Eunsung;Kang, Wonseok;Kim, Sangjin
    • IEIE Transactions on Smart Processing and Computing
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    • 제1권1호
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    • pp.8-16
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    • 2012
  • An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

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Improved k-means Color Quantization based on Octree

  • Park, Hyun Jun;Kim, Kwang Baek
    • 한국컴퓨터정보학회논문지
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    • 제20권12호
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    • pp.9-14
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    • 2015
  • In this paper, we present an color quantization method by complementing the disadvantage of K-means color quantization that is one of the well-known color quantization. We named the proposed method "octree-means" color quantization. K-means color quantization does not use all of the clusters because it initializes the centroid of clusters with random value. The proposed method complements this disadvantage by using the octree color quantization which is fast and uses the distribution of colors in image. We compare the proposed method to six well-known color quantization methods on ten test images to evaluate the performance. The experimental results show 68.29 percent of mean square error(MSE) and processing time increased by 14.34 percent compared with K-means color quantization. Therefore, the proposed method improved the K-means color quantization and perform an effective color quantization.

YCbCr 컬러 영상 변환을 통한 얼굴 영역 자동 검출 (Facial Region Tracking in YCbCr Color Coordinates)

  • 한명희;김경섭;윤태호;신승원;김인영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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    • pp.63-65
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    • 2005
  • In this study, the automatic face tracking algorithm is proposed by using the color and edge information of a color image. To reduce the effects of variations in the illumination conditions, an acquired CCD color image is first transformed into YCbCr color coordinates, and subsequently the morphological image processing operations, and the elliptical geometric measures are applied to extract the refined facial area.

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컬러이미지 검색을 위한 히스토그램 평활화 기반 고유 병발 특징에 관한 연구 (Histogram Equalized Eigen Co-occurrence Features for Color Image Classification)

  • 윤태복;최영미;주문원
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2010년도 추계학술발표대회
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    • pp.705-708
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    • 2010
  • An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

Constant Luminance Signal Coding 에 관한 연구 (A Study on Constant Luminance Signal Coding)

  • 김진서;조맹섭
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2000년도 추계학술발표논문집 (하)
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    • pp.859-862
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    • 2000
  • 본 논문에서는 기존의 TV 시스템에서 사용하는 영상신호의 encoding/decoding 방법과 새롭게 제안되는 constant luminance encoding/decoding 방법을 컴퓨터로 구현하고, 기존의 방법과 제안된 방법으로 재생된 영상의 칼라 정보의 차이에 대한 데이터를 제시한다. 또한 디지털 방송에 적합한 encoding/decoding 시스템의 선택에 대한 고찰도 포함한다.

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칼라 영상 분할을 위한 경계선 보존 영역 병합 방법 (Region Merging Method Preserving Object Boundary for Color Image Segmentation)

  • 유창연;곽내정;김영길;안재형
    • 한국멀티미디어학회논문지
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    • 제7권3호
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    • pp.319-326
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    • 2004
  • 본 논문에서는 물체의 경계선을 고려한 칼라 영상 분할 방법을 제안한다. 제안 방법은 먼저 원영상을 벡터 양자화한 후 양자화된 영상의 인덱스 맵을 이용하여 초기 영역을 설정하였다. 그 후 HSI컬러 공간을 이용한 영역 병합에서 물체의 경계선을 고려하기 위해 경계선 제한 성분을 적용하여 영역들을 병합하였다. 또한 RGB 컬러 공간을 이용하여 HSI 컬러 공간에서 병합되지 않은 영역들을 병합하였다. 그리 고 영역병합 알고리즘을 통해 반복적인 처리를 감소시킴으로써 처리 시간을 줄였다. 실험 결과에서는 다양한 영상에 대해 주요 영역들의 분할 결과 및 처리소요시간에서 우수한 성능을 보였다.

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