• Title/Summary/Keyword: 컬러영역 분할

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Color Image Segmentation of Vitiligo Region (컬러 영상 분석을 통한 백반증 영역 분할)

  • Shin, Seung-Won;Kim, Kyeong-Seop;Lee, Se-Min;Kim, Jeong-Hwan
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.2037-2038
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    • 2011
  • 피부에 나타나는 난치성 질환인 백반증은 심리적인 위축감을 주어 정상적인 생활에 지장을 줄 수 있는 질병이다. 이에 따라서 본 연구에서는 피부에 나타나는 백반증의 진행 상태를 판단하기 위하여 L*a*b* 컬러 공간으로 변환된 피부 영상에 Otsu 임계값 설정 기법을 적용하여 백반증의 발병 영역을 자동으로 판별하는 알고리즘을 제안하였다.

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Integration of Multiple Segmentation Methods based on Evaluation Functions for Segmentation of Visible Human Color Images (평가함수에 의해 혼합된 다수의 분할 방법을 적용한 Visible Human컬러 영상의 분할)

  • 김한영;김동성;강흥식
    • Journal of KIISE:Software and Applications
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    • v.30 no.3_4
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    • pp.308-315
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    • 2003
  • This paper proposes an approach integrating multiple segmentation methods in a systematic way, which can improve overall accuracy without deteriorating accuracy of highly confident segments of boundaries generated by constituent methods. A segmentation method produces boundary segments, which are then evaluated with an evaluation function considering pros/cons of the current and next methods to apply. Boundary segments with low confidence are replaced by a next method while the other segments are kept. These steps are repeated until all segmentation methods are applied. The proposed approach is implemented for the segmentation of muscles in the Visible Human color images. A Balloon method, a minimum cost path finding method, and a Seeded Region Growing method are integrated. The final segmentation results showed improvements in both overall evaluation and segment-based evaluation.

A Color Image Segmentation Using Mean Shift and Region merging method (Mean Shift와 영역병합을 이용한 칼라 영상 분할)

  • Kwak, Nae-Joung;Kwon, Dong-Jin;Kim, Young-Gil
    • Proceedings of the Korea Contents Association Conference
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    • 2006.05a
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    • pp.401-404
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    • 2006
  • Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the proposed method use by merging constraints to decide whether regions is merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

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Estimation of Gamut Boundary based on Modified Segment Maxima to Reduce Color Artifacts (컬러 결점을 줄이기 위한 수정된 segment maxima 기반의 색역 추정)

  • Ha, Ho-Gun;Jang, In-Su;Lee, Tae-Hyoung;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.3
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    • pp.99-105
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    • 2011
  • In this paper, we proposed a method for estimating an accurate gamut based on segment maxima method. According to the number of segments in the segment maxima, a local concavity is generated in the vicinity of lightness axis or a gamut is reduced in high chroma region. It induces artifacts or deterioration of the image quality. To remove these artifacts, the number of segment is determined according to the number of samples. and a local concavity is modified by extending a detected concave point to the line connecting two adjacent boundary points. Experimental results show that the contours in a uniform color region and speckle artifacts from the conventional segment maxima algorithm are removed.

A Study on Fabric Color Mapping for 2D Virtual Wearing System (2D 가상 착의 시스템의 직물 컬러 매핑에 관한 연구)

  • Kwak, No-Yoon
    • Journal of Digital Contents Society
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    • v.7 no.4
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    • pp.287-294
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    • 2006
  • Mass-customization is fast growing a segment of the apparel market. 2D Virtual wearing system is one of visual support tools that make possible to sell apparel before producing and reduce the time and costs related to product development and manufacturing in the world of apparel mass-customization. This paper is related to fabric color mapping method for 2D image-based virtual wearing system. In proposed method, clothing shape section of interest is segmented from a clothes model image using a region growing method, and then mapping a new fabric color selected by user into it based on its intensity difference map is processed. With the proposed method in 2D virtual wearing system, regardless of color or intensity of model clothes, it is possible to virtually change the fabric color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple fabric color combinations for individual styles or entire outfits.

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A New Face Detection Method using Combined Features of Color and Edge under the illumination Variance (컬러와 에지정보를 결합한 조명변화에 강인한 얼굴영역 검출방법)

  • 지은미;윤호섭;이상호
    • Journal of KIISE:Software and Applications
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    • v.29 no.11
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    • pp.809-817
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    • 2002
  • This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

Extended Snake Algorithm Using Color Variance Energy (컬러 분산 에너지를 이용한 확장 스네이크 알고리즘)

  • Lee, Seung-Tae;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.83-92
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    • 2009
  • In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.

Skin segmentation and hand tracking for gesture recognition (제스처 인식을 위한 피부영역 분할기법 및 추적)

  • Chae, Seung-Ho;Seo, Jong-Hoon;Han, Tack-Don
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.371-373
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    • 2012
  • 본 논문에서는 컬러 영상 기반에서 배경에 강인한 피부 영역 검출 기법을 제안하고 손 인식기법을 활용한 응용프로그램을 제안한다. 코드북 모델[1]을 이용하여 배경/전경을 분리하고, 분리된 전경에서 피부색정보를 이용하여 관심영역을 도출한다. 피부 영역을 검출하기 위한 단계에서는 YCbCr, HSV, LUV 색상 모델의 혼합하여 피부색 후보 영역에 대한 임계구간을 통해 강인한 피부 영역을 분할한다. 분할된 영역을 관심영역으로 설정하고 Kalman filter를 이용하여 영역을 추적한다. 결과적으로 복잡하고 고정된 배경에서 조명에 강인한 피부 영역 분할 및 추적이 가능하며 이를 응용한 사용자 인터페이스로 사용될 수 있다.

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Adaptive Region Segmentation using Static/Dynamic Pattern Matching (정적/동적 패턴을 이용한 적응적 영역 분할 방법)

  • Park, Kyoung-Hwan;Lee, Chi-Won;Lee, Chang-Woo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.145-148
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    • 2010
  • 본 논문에서 우리는 도로 영역과 하늘 영역, 그리고 도로와 하늘이 아닌 나머지 영역으로 분할하기 위해 동적인(dynamic) 패턴을 이용한 적응적인(adaptive) 병합 방법을 제안한다. 원본영상에서 Mean Shift 알고리즘과 라벨링(Labeling)을 수행하고 영역을 과분할 한다. 컬러에 의해서 도로와 하늘영역이 검출되지 못하는 영역을 위해서 도로 영역과 하늘 영역에서 동적인 패턴 추출한 후 매칭을 통해 유사 영역을 병합한다. 이것은 도로와 하늘의 정보를 현재 환경에서 적응적으로 추출하는 방법이다. 실험에서 정적인(static) 패턴을 사용해서 병합하는 방법과 동적인 패턴을 사용해서 병합하는 방법을 비교하였다. 그 결과, 동적인 패턴을 사용하였을 때 8.12%의 향상된 성능을 보였다.

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Fast Stereo Matching Using Graphic Hardware (그래픽 하드웨어를 이용한 고속 스테레오 정합)

  • Lee, Sang Hwa;Oh, Jun Ho;Park, Jong-Il
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.11a
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    • pp.262-265
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    • 2010
  • 본 논문에서는 그래픽 하드웨어와 그래픽 프로그램 기술을 이용하여 고속으로 스테레오 영상의 시차를 추정하는 기법을 제안한다. 우선, 컬러 스테레오 영상에 대하여 mean-shift 기법을 이용하여 컬러를 이용한 영역분할을 수행한다. 분할된 컬러 영역 단위로 가중치를 계산함으로써, 화소단위로 가중치를 계산하는 기존의 방식에 비하여 속도를 높일 수 있다. 블록정합함수를 계산하는 과정에서는 슬라이딩 윈도우 방식을 채택하여, 새로 블록안으로 들어오는 화소열과 빠져나가는 화소열의 정합함수값을 가감하여 화소마다 반복적으로 합산되는 정합함수의 계산량을 크게 줄인다. Middlebury 스테레오 영상을 이용하여 실험 및 평가를 수행한 결과, VGA 급 스테레오 영상을 기준으로 10 프레임 이상을 처리하면서도 기존의 적응적인 가중치를 갖는 블록정합 방식의 성능과 유사한 결과를 확인하였다. 이러한 고속화 방법을 통하여, 기존의 적응적인 가중치를 이용한 블록정합 방식에 비하여 훨씬 고속으로 스테레오 정합을 수행할 수 있으며, 실시간 시차추정이 필요한 시스템에 적용하는 것이 가능하다.

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