• Title/Summary/Keyword: color images

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Color Texture Analysis as a Tool for Quantitative Evaluation of Radiation-Induced Skin Injuries

  • Sung Young Lee;Jin Ho Kim;Ji Hyun Chang;Jong Min Park;Chang Heon Choi;Jung-in Kim;So-Yeon Park
    • Journal of Radiation Protection and Research
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    • v.48 no.3
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    • pp.144-152
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    • 2023
  • Background: Color texture analysis was applied as a tool for quantitative evaluation of radiation-induced skin injuries. Materials and Methods: We prospectively selected 20 breast cancer patients who underwent whole-breast radiotherapy after breast-conserving surgery. Color images of skin surfaces for irradiated breasts were obtained by using a mobile skin analyzer. The first skin measurement was performed before the first fraction of radiotherapy, and the subsequent measurement was conducted approximately 10 days after the completion of the entire series of radiotherapy sessions. For comparison, color images of the skin surface for the unirradiated breasts were measured similarly. For each color image, six co-occurrence matrices (red-green [RG], red-blue [RB], and green-blue [GB] from color channels, red [R], green [G], blue [B] from gray channels) can be generated. Four textural features (contrast, correlation, energy, and homogeneity) were calculated for each co-occurrence matrix. Finally, several statistical analyses were used to investigate the performance of the color textural parameters to objectively evaluate the radiation-induced skin damage. Results and Discussion: For the R channel from the gray channel, the differences in the values between the irradiated and unirradiated skin were larger than those of the G and B channels. In addition, for the RG and RB channels, where R was considered in the color channel, the differences were larger than those in the GB channel. When comparing the relative values between gray and color channels, the 'contrast' values for the RG and RB channels were approximately two times greater than those for the R channel for irradiated skin. In contrast, there were no noticeable differences for unirradiated skin. Conclusion: The utilization of color texture analysis has shown promising results in evaluating the severity of skin damage caused by radiation. All textural parameters of the RG and RB co-occurrence matrices could be potential indicators of the extent of skin damage caused by radiation.

A new pyramid structure for progressive transmission of palletized color images (팔레트를 가지는 칼라 영상의 점진적 전송을 위한 새로운 피라미드 자료 구조)

  • Jo, Yeong-U;Kim, Yeong-Mo
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.6
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    • pp.1624-1635
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    • 1996
  • Palletized color images are the dominant type of the image used on Internet and World-Wide Web. In spite of this, most image compression and progressive transmission algorithm have been designed for continuous-tone images. Pallettize images. Palletized images differ from continuous-tone images in such a aspect that values are lookup table indices a new pyramid structure for compression and progressive transmission of a palletized image. In the proposed pyramid structure, the color of a node at higher level is the one that occupies the most part in 4 sons and each node is represented by a type code and several color codes. Since the proposed method do not exploit spatial correlation in an image, it is ideally applied to lossless compression and progressive transmission of palletized images. We have confirmed this through the experimental results.

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Image Retrieval using Modified Color Correlogram (변형된 칼라 코렐로그램을 이용한 영상검색)

  • 안명석;조석제
    • Journal of KIISE:Software and Applications
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    • v.29 no.12
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    • pp.940-946
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    • 2002
  • This paper proposes an image retrieval method to use the modified color correlogram. For retrieving images with less effect of the size variation of the regions in an image, the modified color correlogram is extracted by normalizing auto-correlogram and cross-correlogram of the color correlogram from a color image, and the similarity of two images is calculated by putting the less weight to the auto-correlogram of the modified color correlogram. Because proposed method uses the information of the color correlogram more effectively, we can get better results than that of color correlogram method. In the experiments, the performance of the proposed method is better as compared with that of the color cerrelogram method.

Enhanced Urban Information Recognition through Correction of Shadow Effects (그림자효과 보정을 통한 향상된 도시정보 인식)

  • 손홍규;윤공현;박효근
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.04a
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    • pp.187-190
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    • 2003
  • Due to complexity of diverse features in urban area, accurate feature extraction is laborious task in aerial and satellite imagery. Especially occlusion by buildings, and image distortion of shadow effects make processing more difficult work. In this study, algorithm was presented to correct of shadow effects in aerial color images. This algorithm enables user to accurately interpretate urban information by correction of shadow effects in aerial color images

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Non-linear Interpolation for Color Images

  • Kim, Jong-Ho;Kim, Won-Ki;Yeom, Dong-Hyun;Jeong, Je-Chang
    • 한국정보디스플레이학회:학술대회논문집
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    • 2006.08a
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    • pp.1326-1329
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    • 2006
  • In this paper, we propose a non-linear interpolation of chrominance components based on the property of luminance signals to display color images effectively. The proposed method is more useful, in particular, for the images including stair-typed signal changes around edges. Experimental results show that the proposed method is superior to conventional methods in both objective and subjective performance.

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A Color Texture Feature For Natural Image Retrieval (자연영상 검색을 위한 색질감 특징)

  • 정재웅;권태완;박섭형
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.553-556
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    • 2003
  • In the field of content-based image retrieval, various mathematical low-level features have been proposed to describe the perceptual content of images. Since most of the features are assumed to be independent of each other, one feature is extracted from images without any consideration of the other features. Recently proposed CCE and SCFT taking advantage of the correlation between color and texture have shown relatively good performance. In this paper, the performance of CCE, SCFT, and the traditional regular weighted comparison method are evaluated. Simulation results with natural images have shown that CCE outperforms the other methods.

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Textile image retrieval integrating contents, emotion and metadata (내용, 감성, 메타데이터의 결합을 이용한 텍스타일 영상 검색)

  • Lee, Kyoung-Mi;Park, U-Chang;Lee, Eun-Ok;Kwon, Hye-Young;Cha, Eun-MI
    • Journal of Internet Computing and Services
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    • v.9 no.5
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    • pp.99-108
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    • 2008
  • This paper proposes an image retrieval system which integrates metadata, contents, and emotions in textile images. First, the proposed system searches images using metadata. Among searched images, the system retrieves similar images based on color histogram, color sketch, and emotion histogram. To extract emotion features, this paper uses emotion colors which was proposed on 160 emotion words by H. Nagumo. To enhance the user's convenience, the proposed textile image retrieval system provides additional functions as like enlarging an image, viewing color histogram, viewing color sketch, and viewing repeated patterns.

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Visibility Enhancement of Underwater Image Using a Color Transform Model (색상 변환 모델을 이용한 수중 영상의 가시성 개선)

  • Jang, Ik-Hee;Park, Jeong-Seon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.5
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    • pp.645-652
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    • 2015
  • In underwater, such as fish farm and sea, turbidity is increased by water droplets and various suspended, therefore light attenuation occurs depending on the depth also caused by the scattering effect of light float. In this paper, in order to improve the visibility of underwater images obtained from these aquatic environment, we propose a visibility enhancement method using a haze removal method based on dark channel prior and a trained color transform model. In order to train a color transform model, we used underwater pattern images captured from Pohang and Yeosu, and to measure the performance of the proposed method, we carried out experiment of visibility enhancement using underwater images collected from Yeosu, Geomundo and Philippines. The results show that the proposed method can improve the visibility of underwater images of various locations.

Identification of Transformed Image Using the Composition of Features

  • Yang, Won-Keun;Cho, A-Young;Cho, Ik-Hwan;Oh, Weon-Geun;Jeong, Dong-Seok
    • Journal of Korea Multimedia Society
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    • v.11 no.6
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    • pp.764-776
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    • 2008
  • Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.

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Splitting between Region of Chromatic and Achromatic by Brightness and Chroma (명암과 채도에 의한 색상영역과 비색상영역의 분할)

  • Kwak, Nae-Joung;Hwang, Jae-Ho
    • The Journal of the Korea Contents Association
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    • v.10 no.7
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    • pp.107-114
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    • 2010
  • Color is a sense signal for human to perceive being through light, and the color is divided into chromatic color and achromatic color. Chromatic color has hue, intensity, and saturation, but achromatic color has only intensity among the properties of chromatic color and doesn't have hue and saturation. Therefore it is important to split colors of image into area for human to perceive colors and not to perceive ones based on vision of human being. In this paper, we find a function to split colors of image into chromatic region of chromatic color region and achromatic region of achromatic color region. First, the input image of RGB color space is converted into the image of HSI color space in consideration of human vision and get a binary image from the converted image. After then, a function to split colors into ROC(ROC: Region of chromatic.) and ROA(ROA:Region of achromatic) is yield. It is difficult to split color of a general image into ROC and ROA. Therefore, to get the chromatic area and achromatic area, we make gradient images to have all range of intensity and range of saturation and to have a little range of hue and yield the function. The evaluation is tested using subjective-quality by 50 non-experts for result images of test images and general images. The results of the proposed method get better 27.5~32.96% than these of the conventional method