• The Journal of Korean Academy of Prosthodontics
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• v.16 no.1
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• pp.38-44
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• 1978

Color is an important factor in dental esthetics. Application of natural tooth color will not fail to produce pleasing results. But a standardized method of shade matching has not been adopted. If we are to overcome the color matching problem in dentistry, an understanding of the nature of color and light is essential. The purpose of this study was to compare the effects of different light sources and different background colors on the ability of observers to correctly match shades of artifical teeth. And observation was made to determine if the time spent in making a shade match was a factor in the correctness of the response. A test method was devised and 50 individuals made observations which were recorded and analyzed. $X^2$-test gave results indicating that the time factor had no effect on the response made. An analysis of variance showed the following effects significant at the five percent level; (1) light source (2) background color (3) subject. The following conclusions can be drawn from this study; (1) The time spent in making shade selection is not a factor in the correctness of the selections. (2) The light source used is an important factor in matching tooth shade; and there is no significant difference between the light sources in shade matching. (3) Under the conditions of this study, the greatest accuracy in shade matching was obtained on the brown background.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.610-619
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• 2015

*In this paper, we propose a real-time face tracking system using an adaptive face detector and a tracking algorithm. An image is divided into the regions of background and face candidate by a real-time updated skin color identifying system in order to accurately detect facial features. The facial characteristics are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted by Principal Component Analysis (PCA), and the interpreted principal components are processed by Support Vector Machine (SVM) that classifies into facial and non-facial areas. The movement of the face is traced by Kalman filter and Mean shift, which use the static information of the detected faces and the differences between previous and current frames. The proposed system identifies the initial skin color and updates it through a real-time color detecting system. A similar background color can be removed by updating the skin color. Also, the performance increases up to 20% when the background color is reduced in comparison to extracting features from the entire region. The increased detection rate and speed are acquired by the usage of Kalman filter and Mean shift.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.7
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• pp.851-861
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• 2003

The objectives of this study were to investigate the effect of perceiver's fashion involvement, clothing color, and background of object person on image perceptions of clothing, and to examine how clothing color preference vary according to perceiver's fashion involvement. Subjects were 273 college women in the metropolitan area of Seoul. The T-shirt was changed into 11 colors by using the CAD system. Five factors were derived to account for the dimensions of image perception. These were individuality, elegance, femininity, activity, and neatness. Perceiver's fashion involvement gave a significant influence on perception of individuality. Clothing color gave significant influences on 5 image dimensions. White and beige were evaluated neat image. Neatness factor had an interaction effect by fashion involvement and clothing color. The high involvement group evaluated white and beige shirt more neatly, and orange and yellow less neatly than the low involvement group. Individuality and elegance had an interaction effect by fashion involvement and background of object person. The high involvement group liked red, violet, and black shirt more than the low involvement. Refined and becomingness image gave significant influences on clothing color preference in both high and low involvement groups.

• Fisheries and Aquatic Sciences
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• v.17 no.3
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• pp.325-337
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• 2014

To assess the functional structure of prepro-melanin-concentrating hormone (pMCH), we isolated and cloned pMCH (of-pMCH) mRNA from the brain of the olive flounder, Paralichthys olivaceus, and compared its amino acid sequence with those from other animals. In addition, to examine whether activation of the brain of-pMCH gene is influenced by background color, density, and feeding, we compared pMCH mRNA activities against different background colors (bright and dark) and at different densities (100% PCA and 200% PCA). To examine whether the pMCH gene is related with malpigmentation of blind-side skin and appetite, we compared pMCH gene expression between ordinary and hypermelanic flounders, and between feeding and fasting flounders. The of-pMCH cDNA was 405 bp in the open reading frame [ORF] and encoded a protein of 135 amino acids; MCH was 51 bp in length and encoded a protein of 17 amino acids. An obvious single band of the expected size was obtained from the brain and pituitary by RT-PCR. In addition, of-pMCH gene activity was significantly higher in the bright background only at low density (< 100% PCA) making the ocular skin of fish whitening, and in ordinary fish. However, the gene activity was significantly decreased in dark background, at high density (>200% PCA), and in hypermelano fish. These results suggest that skin whitening camouflage of the flounder is induced by high MCH gene activity, and the density disturbs the function of background color in the physiological color change. Moreover, our data suggest that a low level of MCH gene activity may be related to malpigmentation of the blind-side skin. In feeding, although pMCH gene activity was significantly increased by feeding in the white background, the pMCH gene activity in the dark background was not influenced by feeding, indicating that the MCH gene activity increased by feeding can be offset by dark background color, or is unaffected by appetite. In conclusion, this study showed that MCH gene expression is related to ocular-skin whitening camouflage and blind-skin hypermelanosis, and is influenced by background color and density.

• Restorative Dentistry and Endodontics
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• v.24 no.4
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• pp.585-603
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• 1999

Esthetic availabilities used as an esthetic restorative maternals can be determined by the optical coincidence among materials, enamel and dentin. Enamel is highly translucent. That's why esthetic materials need to correspond the close translucency of enamel. But the translucent materials are affected by the background color. So it should be predicted that the color of estorative materials depend on the any thickness and the spectral reflectance of the background on which they are placed. The object of this investigation, under above hypothesis, was to determine and analyze how they affect the final color according to the thickness, translucency and background color (white, black and dentin) fill three commercial light cured composite resins(Charisma, Spectrum TPH and Z100). And correlation was analyzed to find out the possibility of the prediction when using the certain background color and thickness of materials. Followings are the result 1. The I shade of CHA showed the lowest contrast ratio($Co_7$) while the B3 shade of Z100 showed the highest contrast ratio(p<0.05). 2. The value of $L^*$ and $b^*$ on the white and dentin background is increased with decreasing thickness. And there are significant relationships between increasing thickness and each value(R>0.085). But there is a little change of $L^*$ and $b^*$ value on the black background regardless of the thickness(p>0.05). 3. For the $a^*$ value, there was little difference in values as a function of thickness and changed irregularly regardless of thickness in all background. 4. The pattern of increasing value of $L^*$ and $b^*$ with decreasing thickness was similar to the group of white and dentin background. In both dentin one showed lesser change of value. 5. The values of $L^*a^*b^*$ measured on the different background with same thickness showed the recognizable color difference(${\Delta}E^*$>2) when the thickness was below 2.6mm. 6. Contrast ratio was increased with increasing thickness with significant relationship (R>0.9). 7. Spectral reflectance of composite resins that calculated from Kubelka-Munk equation was showed little difference compared with observed value w1th decreasing thickness.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.407-412
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• 2008

Color segmentation is one of the most challenging problems in image processing especially in case of handling the images with cluttered background. Great amount of color segmentation methods have been developed and applied to real problems. In this paper, we suggest a new methodology. Our approach is focused on background extraction, as a complimentary operation to standard foreground object segmentation, using self-organizing feature selective property of unsupervised self-learning paradigm based on the competitive algorithm. The results of our studies show that background segmentation can be achievable in efficient manner.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.841-847
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• 2016

To study the influence of background color and substratum on hypermelanosis of starry flounder, we compared the daily food intake (DFI), the feed efficiency (FE), the survival, the growth, the ratio of pigmented area on the blind side and the ratio of hypermelanic fish duplicately reared for 180 days in dark-green FRP aquarium (control), white FRP aquarium together with dark-green substratum. The ratio of pigmented area on the blind side was significantly higher at the dark-green group than at the white group. DFI, FE and growth were higher in the dark-green substratum. Pigmented area rate and ratio of hypermelanic fish were significantly higher at the dark green group than at the high dark-green substratum. The results suggest that bright tank color and substratum bottom could inhibit the hypermelanosis.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.114-127
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• 2017

This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test color images reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.