• 제목/요약/키워드: color transformation

검색결과 302건 처리시간 0.022초

경계 중요도 맵 및 영역 병합에 기반한 칼라 영상 분할 (Color Image Segmentation Based on Edge Salience Map and Region Merging)

  • 김성영
    • 한국컴퓨터정보학회논문지
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    • 제12권3호
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    • pp.105-113
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    • 2007
  • 본 논문에서는 경계 중요도 맵과 영역 병합에 의한 영상 분할 방법을 제안한다. 경계 중요도 맵은 텍스쳐 경계 강도와 칼라 경계 강도의 조합에 의해 생성한다. 텍스쳐 경계 강도는 가버 필터 뱅크를 사용하여 다중 스케일과 방향에 따른 필터링 결과를 병합하여 생성하며 칼라 경계 강도는 HSI 칼라 모델의 H 성분에 대해 계산한다. 경계 중요 맵 영상에 대해서는 Watershed 변환을 통해 사전 영상 분할을 수행한다. Watershed 변환에 의한 영상 분할은 영역들이 과잉 분할되는 현상이 나타나므로 이를 개선하여 최종 영상 분할 결과를 생성한다. 이를 위해 우선 모폴로지 연산을 사용하여 경계 중요도 맵 영상에 대한 컨트라스트 향상과 마커 영역을 생성한다. 모폴로지 연산으로 과잉 분할 영역은 줄어들지만 여전히 상당수 존재하게 되므로 이를 극복하기 위해 영역 병합 과정을 수행한다. 영역 병합 단계에서는 영역 내부의 평균 칼라 및 가버 텍스쳐 벡터를 함께 사용함으로써 효과적으로 과잉 분할된 영역을 병합할 수 있도록 하였다. 제안한 방법은 다양한 자연 영상에 대해 실험하였으며 기존 방법과 결과를 비교하여 성능의 우수성을 확인하였다.

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COLORNET: Importance of Color Spaces in Content based Image Retrieval

  • Judy Gateri;Richard Rimiru;Micheal Kimwele
    • International Journal of Computer Science & Network Security
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    • 제23권5호
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    • pp.33-40
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    • 2023
  • The mainstay of current image recovery frameworks is Content-Based Image Retrieval (CBIR). The most distinctive retrieval method involves the submission of an image query, after which the system extracts visual characteristics such as shape, color, and texture from the images. Most of the techniques use RGB color space to extract and classify images as it is the default color space of the images when those techniques fail to change the color space of the images. To determine the most effective color space for retrieving images, this research discusses the transformation of RGB to different color spaces, feature extraction, and usage of Convolutional Neural Networks for retrieval.

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

  • 김치용
    • 전기전자학회논문지
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    • 제18권3호
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    • pp.403-408
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    • 2014
  • 본 논문은 Varying Interpolator를 개선하여 다수의 Pixel을 한 번에 처리할 수 있는 Rasterizer 구조를 제안한다. 설계한 Rasterizer의 Varying Interpolator는 한 번에 16 Pixel을 처리 할 수 있으며 최대 64개의 색상을 출력으로 가진다. 또한 Rasterizer의 연산을 행렬연산 및 행렬변환으로 구성하여 연산의 중복성을 줄이고 재사용성을 높여 Rasterizer의 처리 속도를 높였다. 제안하는 구조의 Rasterizer 는 기존의 연구와 비교하여 색상 보간은 11%, Rasterizer 전체 처리 속도는 17% 향상된 성능을 보였다.

COUNTING OF FLOWERS BASED ON K-MEANS CLUSTERING AND WATERSHED SEGMENTATION

  • PAN ZHAO;BYEONG-CHUN SHIN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제27권2호
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    • pp.146-159
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    • 2023
  • This paper proposes a hybrid algorithm combining K-means clustering and watershed algorithms for flower segmentation and counting. We use the K-means clustering algorithm to obtain the main colors in a complex background according to the cluster centers and then take a color space transformation to extract pixel values for the hue, saturation, and value of flower color. Next, we apply the threshold segmentation technique to segment flowers precisely and obtain the binary image of flowers. Based on this, we take the Euclidean distance transformation to obtain the distance map and apply it to find the local maxima of the connected components. Afterward, the proposed algorithm adaptively determines a minimum distance between each peak and apply it to label connected components using the watershed segmentation with eight-connectivity. On a dataset of 30 images, the test results reveal that the proposed method is more efficient and precise for the counting of overlapped flowers ignoring the degree of overlap, number of overlap, and relatively irregular shape.

Color Image Enhancement Using a Retinex Algorithm with Bilateral Filtering for Images with Poor Illumination

  • Mulyantini, Agustien;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제19권2호
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    • pp.233-239
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    • 2016
  • Color enhancement basically deals with color manipulation in digital images. Recently, the technique has become widely used as a result of the increasing use of digital cameras. Retinex-based colorenhancement algorithms are a popular technique. In this paper, retinex with bilateral filtering is proposed to improve the quality of poorly illuminated images. Generally, it consists of three main steps: first, a retinex-based algorithm with color restoration; second, transformation mapping using histogram matching; and finally, smoothing the image using a bilateral filter. The experimental results demonstrate that the proposed method can successfully enhance image contrast while avoiding the halo effect and maintaining the color distribution in the image.

적록색맹 모사 영상 데이터를 이용한 딥러닝 기반의 위장군인 객체 인식 성능 향상 (Performance Improvement of a Deep Learning-based Object Recognition using Imitated Red-green Color Blindness of Camouflaged Soldier Images)

  • 최근하
    • 한국군사과학기술학회지
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    • 제23권2호
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    • pp.139-146
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    • 2020
  • The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

칼라 항상성에 기초한 칼라영상 향상 (Color Image Enhancement Based on Color Constancy)

  • 배성호;김정엽;권갑현;하영호
    • 전자공학회논문지B
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    • 제30B권5호
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    • pp.103-108
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    • 1993
  • An image can be largely corrupted by the ambient illuminant, so that the image enhancement to restory natural color without respect to the ambient illuminant is needed. It this paper, a new color image enhancement technique based on color constancy is proposed. To enhance the image quality, higher volues of contrast and saturation are preferred, but their excessive values make an image unnatural. Since the color constancy processing preserves only hue, while reducing the dynamic range of lightness and saturation,the technique is needed in order to compensate this phenomenon. The proposed method transforms and increases lightness and saturation simultaneously to avoid the complexity in the related transformation by analyzing the relationship between the RGB and modified IHS coordinate system.

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색상요소를 고려한 얼굴검출에 대한 연구 (A study of face detection using color component)

  • 이정하;강진석;최연성;김장형
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2002년도 추계종합학술대회
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    • pp.240-243
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    • 2002
  • 본 논문에서는 칼라 이미지에서 색상 요소를 기초로 하여 얼굴영역을 추출하고 얼굴의 특징요소를 추출하는 방법을 제안한다. 얼굴 영역을 추출하기 위하여 일반적인 얼굴색상분포를 이용하여 색상변환을 하였다. 얼굴 특성요소를 찾기 위하여 윤곽선검출을 이용하였다. 얼굴영역의 상단부분에서 눈의 요소를 찾고, 눈과 입의 지정학적 위치를 이용하여 입의 후보영역을 지정하고 입을 찾도록 하였다. 검색영역을 좁혀 계산량을 줄임으로서 탐색시간을 줄일 수 있고, 일반적인 얼굴색상분포를 이용하여 얼굴 영역을 검출함으로서 얼굴표정, 얼굴색변화, 기울짐에 대해서도 얼굴영역을 검출할 수 있었다.

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Optimization of Parameters for GUS Gene Transformation of Porphyra yezoensis by Particle Bombardment

  • Nam, Bo-Hye;Park, Jung-Youn;Jin, Deuk-Hee;Hong, Yong-Ki
    • Fisheries and Aquatic Sciences
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    • 제9권4호
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    • pp.135-139
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    • 2006
  • We optimized the biological and physical parameters for DNA delivery into thalli of the red alga Porphyra yezoensis using a particle bombardment device. The efficiency of transformation was determined using the ${\beta}-glucuronidase$ (GUS) assay. The optimal helium pressure, distance of tungsten particle flight, and ratio of DNA to tungsten particles were $23kgf/cm^2$, 8 cm, and $5{\mu}g/mg$ tungsten, respectively. During bombardment, osmotic treatment with a mixture of 0.6 M mannitol and sorbitol increased the efficiency of GUS transformation. After 2 days, the blue color indicating GUS activity was observed using a histochemical assay.

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

  • 배준;김재민;김성인
    • 제어로봇시스템학회논문지
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    • 제12권2호
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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.