• The Journal of Korean Medicine
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• v.37 no.3
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• pp.27-38
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• 2016

Objectives: According to Korean Medicine theory, the skin color of LU10 serves as a diagnostic clue to dyspeptic symptoms. The aims of this study were (1) to find the difference of skin color in LU10 region between functional dyspepsia (FD) and healthy control (HC) and (2) to examine the relationship between LU10 skin color parameters and dyspeptic symptoms. Methods: 39 participants (29 FD and 10 HC) have participated in this study. They were asked to complete gastrointestinal scale (GIS), gastrointestinal symptom rating scale (GSRS), Nepean dyspepsia index (NDI), functional dyspepsia-related quality of life (FD-QoL), visual analogue scale (VAS) for dyspeptic symptoms, food retention questionnaire (FRQ) and cold heat questionnaire (CHQ). $L^*$ (luminance), $a^*$ (red-green balance) and $b^*$ (yellow-blue balance) values of LU10 region were calculated through digital images of the participant's hand. Then we evaluated test-retest reliability of $L^*$, $a^*$ and $b^*$ values of LU10 region. Additionally, we compared $L^*$, $a^*$ and $b^*$ values of LU10 between FD and HC, and examined the relationship between LU10 color parameters and seven questionnaires scores. Results: Only $L^*$ values in LU10 region were significantly higher in FD compared with HC. GIS scores and the subset scores of NDI had a positive correlation with $L^*$ values significantly. Correlation coefficients of test-retest reliability of skin color measurement of LU10 ranged from 0.871 to 0.936 representing very strongly statistically significant (P<0.001). Conclusions: We confirmed the difference of skin color in LU10 region between FD and HC, and relationship between LU10 skin color parameters and dyspeptic symptoms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.930-938
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• 2005

We propose a content-based image retrieval(CBIR) method based on an efncient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelograrn is chosen which is blown to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is hewn to measure local intensity variations well and measure local texture smoothness well, respectively. The texture features are obtained in a wavelet pyramid of the luminance component of a color image. The extracted features are combined for efficient similarity computation by the normalization depending on their dimensions and standard deviation vectors. Experimental results show that the proposed method yielded average $8\%\;and\;11\%$ better performance in precision vs. recall than the method using BDIPBVLC moments and the method using color autocorrelograrn, respectively and yielded at least $10\%$ better performance than the methods using wavelet moments, CSD, color histogram. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.986-995
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• 2009

Color affects people in their various combinations of hue, saturation and value. On the other hand, people may feel different emotion from the same color. If we can introduce these characteristics of color and people's emotion about color to emotion-based digital technologies and their contents, we can effectively draw users' interest and immersion to the contents. In this paper, we will show how people feel about color and present a method of image coloring that reflects the user's preference. First, we define basic templates that reflect the relationship between color and emotion, and then perform an image coloring. To reflect user's preference, we compute weights for hue, saturation and value through the experiments on each subject's preference about hue, saturation and value. The image coloring for each subject's taste will be drawn by updating the weights of hue, saturation and value. Through the results of experiments and surveys, we found that people were more satisfied with the transformation of the templates which reflected user's preference than the one that did not.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.44-50
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• 2006

This study has proposed a method of content-based image retrieval using object region in order to overcome disadvantages of existing color histogram methods. The existing color histogram methods have a weak point of reducing accuracy, because these have both a quantization error and an absence of spatial information. In order to overcome this problem, we convert a color information to a HSV space, quantize hue factor being pure color information, and calculate histogram. And then we use hue for retrieval feature that is robust in brightness, movement, and rotation. To solve the problem of the absence of spatial information, we select object region in terms of color feature and region correlation. And we use both the edge and the DC in the selected region for retrieving. As a result of experiment with 1,000 natural color images, the proposed method shows better precision and recall than the existing methods.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.394-400
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• 2012

SURF is a robust local invariant feature descriptor and has been used in many applications such as object recognition. Even though this algorithm has similar matching accuracy compared to the SIFT, which is another popular feature extraction algorithm, it has advantage in matching time. However, these descriptors do not consider relative location information of extracted interesting points to guarantee rotation invariance. Also, since they use gray image of original color image, they do not use the color information of images, either. In this paper, we propose a method for improving matching performance of SURF descriptor using the color and relative location information of interest points. The location information is built from the angles between the line connecting the centers of interest points and the orientation line constructed for the center of each interest points. For the color information, color histogram is constructed for the region of each interest point. We show the performance of our scheme through experiments.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.54-61
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• 2009

This paper proposes a skin segmentation method based on region histograms of the color quantization map. First, we make a quantization map of the image using the JSEG algorithm and detect the skin pixel. For the skin region detection, the similar neighboring regions are set by its similarity of the size and location between the previous frame and the present frame from the each region of the color quantization map. Then we compare the similarity of histogram between the color distributions of each quantized region and the skin color model using the histogram distance. We select the skin region by the threshold value calculated automatically. The skin model is updated by the skin color information from the selected result. The proposed algorithm was compared with previous algorithms on the ECHO database and the continuous images captured under time varying illumination for adaptation test. Our approach shows better performance than previous approaches on skin color segmentation and adaptation to varying illumination.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.1-8
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• 2009

Image compression schemes, such as JPEG and JPEG2000, degrade the Quality of a reconstructed image due to their lossy characteristics. Accordingly, this paper investigates the relationship between the compression ratio and the gamut variation for a reconstructed image using JPEG and JPEG2000. To analyze the relationship between compression ratio and gamut variation, i.e. the hue and chroma shift in the uniform color space, eighteen color samples from the Macbeth ColorChecker are initially used. Based on the color shift phenomenon for the color samples, twelve natural color images, classified into two groups depending on four color attributes, are also used to investigate the relationship between the level of compression and the variation in the gamut area. As a results, through the experiments, least square method is applied to obtain the fitting curves as an equation minimizing the error between the real data and its corresponding approximated values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.375-382
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• 2010

In this paper, we propose the simplified and improved system of One Color Detector to protect color distortion of simple color images in the processed of Auto White Balance (AWB). The proposed One Color Detector is based on Grayworld algorithm which controls color compensation except one color in simple image and widely applies for mobile phone camera because of high efficiency. This system can be suitable for diverse image size, and let user control the threshold in diverse size and environments compared with conventional system. Also the hardware size of the proposed system is reduced by 80% over that of the conventional one.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.579-586
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• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3718-3726
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• 1999

Color image is more effective than gray one in human visual perception. Therefore, color image processing becomes important area. Color images are often corrupted by noises due to the input sensor, channel transmission errors and so on. Some filtering techniques such as vector median, mean filter, and vector $\alpha-trimmed$ mean filter have been used for color noise removal. Among them, vector $\alpha-trimmed$ mean filter gave the best performance in the mixed color noise. But, there are edge shift and blurring effect because vector $\alpha-trimmed$ mean filter is uniformly processed across the image. So, we proposed a conditional fuzzy cluster filter to improve this problems. Simulation results showed that the proposed scheme improves the NCD measure and visual quality over the conventional vector $\alpha-trimmed$ mean filter in the mixed color noise.