• 제목/요약/키워드: Local Color

검색결과 632건 처리시간 0.025초

Color Enhancement in Images with Single CCD camera in Night Vision Environment

  • Hwang, Wonjun;Ko, Hanseok
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.58-61
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    • 2000
  • In this paper, we describe an effective method to enhance the color night images with spatio-temporal multi-scale retinex focused to the Intelligent Transportation System (ITS) applications such as in the single CCD based Electronic Toll Collection System (ETCS). The basic spatial retinex is known to provide color constancy while effectively removing local shades. However, it is relatively ineffective in night vision enhancement. Our proposed method, STMSR, exploits the iterative time averaging of image sequences to suppress the noise in consideration of the moving vehicles in image frame. In the STMSR method, the spatial term makes the dark images distinguishable and preserves the color information day and night while the temporal term reduces the noise effect for sharper and clearer reconstruction of the contents in each image frame. We show through representative simulations that incorporating both terms in the modeling produces the output sequential images visually more pleasing than the original dim images.

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Visible Distortion Predictors Based on Visual Attention in Color Images

  • Cho, Sang-Gyu;Hwang, Jae-Jeong;Kwak, Nae-Joung
    • Journal of information and communication convergence engineering
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    • 제10권3호
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    • pp.300-306
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    • 2012
  • An image attention model and its application to image quality assessment are discussed in this paper. The attention model is based on rarity quantification, which is related to self-information to attract the attention in an image. It is relatively simpler than the others but results in taking more consideration of global contrasts between a pixel and the whole image. The visual attention model is used to develop a local distortion predictor, named color visual differences predictor (CVDP), in color images in order to effectively detect luminance and color distortions.

Text Extraction in HIS Color Space by Weighting Scheme

  • Le, Thi Khue Van;Lee, Gueesang
    • 스마트미디어저널
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    • 제2권1호
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    • pp.31-36
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    • 2013
  • A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.

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전통적 사진 기법에 기반한 컬러 영상의 흑백 변환 (Color2Gray using Conventional Approaches in Black-and-White Photography)

  • 장혁수;최민규
    • 한국컴퓨터그래픽스학회논문지
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    • 제14권3호
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    • pp.1-9
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    • 2008
  • 본 논문에서는 전통적인 사진 기법에 기반하여 대비가 뚜렷한 흑백 영상을 얻기 위한 새로운 방법을 제안한다. 사진가들은 대비가 뚜렷한 흑백 사진을 얻기 위해 촬영 시 대비 필터(consrast filter)를 사용하여 특정 색이 부각된 흑백 필름을 얻고, 인화 시 버닝(burning)과 닷징(dodging) 같이 국지적 노출을 조절하는 기법을 사용하였다. 본 논문에서는 이러한 흑백 사진 기법에 대한 디지털 버전을 제안하고 이에 기반하여 영상의 시각적 특징을 최대한 유지하는 최적화 기법을 제안한다. 또한, 인접 픽셀간의 유사 가중치를 이용하여 경계를 감안한 연속적인 국지적 노출을 얻게 한다. 제안한 기법은 GPU상에서 구현 가능하며 메가픽셀 영상에 대해서도 시각적 특징을 유지하는 흑백 영상을 대화적 시간 안에 획득할 수 있다.

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컬러정보와 국부 최적 임계치 기법을 이용한 얼굴 영역 검출 (Facial Region Detection by using Color Information and Shape-resolving Local Thresholding)

  • 박상근;박영태
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (2)
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    • pp.553-555
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    • 2003
  • 사람의 얼굴을 검출 및 인식을 하는 여러 가지 다양한 알고리즘이 소개되고 있다. 본 논문에서는 사람의 피부색을 이용한 컬러정보(Color Information)와 국부 최적 임계치 기법을 사용하여 얼굴의 형상정보를 검출하고 얼굴 영역을 검출하는 방법을 사용한다. 컬러정보를 사용하여 얼굴의 후보영역을 선정한 후에 그 후보영역에서 얼굴의 특징인 눈, 눈썹, 입을 찾는 방법을 제안한다. 피부색은 일정한 분포를 가지고 있기 때문에 후보영역을 비교적 정확히 찾을 수 있으며, 국부 최적 임계치 기법은 효과적인 얼굴 특징 검출방법이다.

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화질 향상을 위한 색역 사상 (Gamut Mapping Algorithm for Image Quality Enhancement)

  • 김재철;허태욱;조맹섭
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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    • pp.251-254
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    • 2002
  • Currently many devices reproduce electronic images in a variety of ways. However, the colors that are reproduced are different from the original color due to the differences in the gamut between devices. In this paper, a gamut mapping method utilizing a simultaneous mapping function and a lightness rescaling is proposed. This method enhance the local-color characteristics and lightness contrast. The experimental result shows that the overall contrast and the colorfulness were increased.

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Comparison of Growth Performance, Carcass Characteristics and Meat Quality of Korean Local Chickens and Silky Fowl

  • Choo, Y.K.;Kwon, H.J.;Oh, S.T.;Um, J.S.;Kim, B.G.;Kang, C.W.;Lee, S.K.;An, B.K.
    • Asian-Australasian Journal of Animal Sciences
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    • 제27권3호
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    • pp.398-405
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    • 2014
  • This study was conducted to compare growth performance, carcass characteristics and meat quality of 4 breeds of local chicken. A total of 480 1-d-old chicks were distributed to 16 pens, with 4 treatments of breed, 4 replicates and 30 chicks per pen. Three Korean local breeds of white-mini broiler, Hanhyup-3-ho, and Woorimatdag, and a breed of silky fowl were raised under identical rearing and feeding conditions for 31-d, 37-d, 36-d, and 59-d, respectively. The BW and feed consumption on a pen basis were weekly measured for all pens, and ADFI, ADG and gain:feed were calculated for each pen. The ADFI and ADG of 3 breeds of Korean local chicken were greater than those of silky fowl (p<0.05). Within the Korean local breeds, ADFI of white-mini broiler was the highest (p<0.05), and ADG of Hanhyup-3-ho and white-mini broiler was the highest (p<0.05). Gain:feed of silky fowl was less than that of the 3 breeds of Korean local chicken. The carcass and breast yield of white-mini broiler were the greater than those of other breeds (p<0.05). The breast meat color (CIE $L^*$, $a^*$, and $b^*$) of 3 breeds of Korean local chicken were higher than that of silky fowl (p<0.05). The breast meat of Hanhyup-3-ho had greater cooking loss (p<0.05), whereas water holding capacity and pH were less than those of other breeds (p<0.05). The color score of 3 breeds of Korean local chicken was higher than that of silky fowl (p<0.05). Woorimatdag had a higher score on tenderness (p<0.05), whereas flavor score was less than that of other breeds (p<0.05). In conclusion, 4 local breeds of chicken have some unique features and seem to have more advantages, and this information can help consumers who prefer healthy and premium chicken meat.

선형 MSR을 이용한 역광 영상의 명암비 향상 알고리즘 (Contrast Enhancement Algorithm for Backlight Images using by Linear MSR)

  • 김범용;황보현;최명렬
    • 전기학회논문지P
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    • 제62권2호
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    • pp.90-94
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    • 2013
  • In this paper, we propose a new algorithm to improve the contrast ratio, to preserve information of bright regions and to maintain the color of backlight image that appears with a great relative contrast. Backlight images of the natural environment have characteristics for difference of local brightness; the overall image contrast improvement is not easy. To improve the contrast of the backlight images, MSR (Multi-Scale Retinex) algorithm using the existing multi-scale Gaussian filter is applied. However, existing multi-scale Gaussian filter involves color distortion and information loss of bright regions due to excessive contrast enhancement and noise because of the brightness improvement of dark regions. Moreover, it also increases computational complexity due to the use of multi-scale Gaussian filter. In order to solve these problems, a linear MSR is performed that reduces the amount of computation from the HSV color space preventing the color distortion and information loss due to excessive contrast enhancement. It can also remove the noise of the dark regions which is occurred due to the improved contrast through edge preserving filter. Through experimental evaluation of the average color difference comparison of CIELAB color space and the visual assessment, we have confirmed excellent performance of the proposed algorithm compared to conventional MSR algorithm.

A Novel Perceptual Hashing for Color Images Using a Full Quaternion Representation

  • Xing, Xiaomei;Zhu, Yuesheng;Mo, Zhiwei;Sun, Ziqiang;Liu, Zhen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권12호
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    • pp.5058-5072
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    • 2015
  • Quaternions have been commonly employed in color image processing, but when the existing pure quaternion representation for color images is used in perceptual hashing, it would degrade the robustness performance since it is sensitive to image manipulations. To improve the robustness in color image perceptual hashing, in this paper a full quaternion representation for color images is proposed by introducing the local image luminance variances. Based on this new representation, a novel Full Quaternion Discrete Cosine Transform (FQDCT)-based hashing is proposed, in which the Quaternion Discrete Cosine Transform (QDCT) is applied to the pseudo-randomly selected regions of the novel full quaternion image to construct two feature matrices. A new hash value in binary is generated from these two matrices. Our experimental results have validated the robustness improvement brought by the proposed full quaternion representation and demonstrated that better performance can be achieved in the proposed FQDCT-based hashing than that in other notable quaternion-based hashing schemes in terms of robustness and discriminability.

슈퍼픽셀의 밀집도 및 텍스처정보를 이용한 DBSCAN기반 칼라영상분할 (A Method of Color Image Segmentation Based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) Using Compactness of Superpixels and Texture Information)

  • 이정환
    • 디지털산업정보학회논문지
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    • 제11권4호
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    • pp.89-97
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    • 2015
  • In this paper, a method of color image segmentation based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) using compactness of superpixels and texture information is presented. The DBSCAN algorithm can generate clusters in large data sets by looking at the local density of data samples, using only two input parameters which called minimum number of data and distance of neighborhood data. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. Each superpixel is consist of pixels with similar features such as luminance, color, textures etc. Superpixels are more efficient than pixels in case of large scale image processing. In this paper, superpixels are generated by SLIC(simple linear iterative clustering) as known popular. Superpixel characteristics are described by compactness, uniformity, boundary precision and recall. The compactness is important features to depict superpixel characteristics. Each superpixel is represented by Lab color spaces, compactness and texture information. DBSCAN clustering method applied to these feature spaces to segment a color image. To evaluate the performance of the proposed method, computer simulation is carried out to several outdoor images. The experimental results show that the proposed algorithm can provide good segmentation results on various images.