• Title/Summary/Keyword: Color Transformation

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

  • Kim, Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.105-113
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    • 2007
  • In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

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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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    • v.23 no.5
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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.

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.

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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    • v.27 no.2
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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
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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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.

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

  • Choi, Keun Ha
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.2
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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.

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

  • 배성호;김정엽;권갑현;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.5
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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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A study of face detection using color component (색상요소를 고려한 얼굴검출에 대한 연구)

  • 이정하;강진석;최연성;김장형
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.240-243
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    • 2002
  • In this paper, we propose a face region detection based on skin-color distribution and facial feature extraction algorithm in color still images. To extract face region, we transform color using general skin-color distribution. Facial features are extracted by edge transformation. This detection process reduces calculation time by a scale-down scanning from segmented region. we can detect face region in various facial Expression, skin-color deference and tilted face images.

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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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    • v.9 no.4
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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.

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.