• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.18-22
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• 2004

It is difficult to understand a person's emotion, since it is subjective and vague. Therefore, we are proposing a method by which will effectively classify human emotions into two types (that is, single emotion and composition emotion). To verify validity of te proposed method, we conducted two experiments based on general inference and $\alpha$-cut, and compared the experimental results. In the first experiment emotions were classified according to fuzzy inference. On the other hand in the second experiment emotions were classified according to $\alpha$-cut. Our experimental results showed that the classification of emotion based on a- cut was more definite that that based on fuzzy inference.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.127-133
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• 2005

An f-coloring of a graph G = (V, E) is a coloring of edge set E such that each color appears at each vertex v $\in$ V at most f(v) times. The minimum number of colors needed to f-color G is called the f-chromatic index $\chi'_f(G)$ of G. Any graph G has f-chromatic index equal to ${\Delta}_f(G)\;or\;{\Delta}_f(G)+1,\;where\;{\Delta}_f(G)\;=\;max\{{\lceil}\frac{d(v)}{f(v)}{\rceil}\}$. If $\chi'_f(G)$= ${\Delta}$f(G), then G is of $C_f$ 1 ; otherwise G is of $C_f$ 2. In this paper, the classification problem of complete graphs on f-coloring is solved completely.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.67-74
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• 1999

A prototype cut-flower sorter was developed and tested for its performance with five varieties of roses. Support plates driven by a chain mechanism transported the roses into an image inspection chamber. Color image processing algorithms were developed to evaluate the length, thickness, and straightness of stem and color, height, and maturity of bud. The average absolute errors of the system for the measurements of stem length, stem thickness, and height of bud were 19.7 mm, 0.5 mm, and 3.8 mm, respectively. The results of classification by the sorter were compared with those of a human inspector for straightness of stem and maturity of bud. The classification error for the straightness of stem was 8.6%, when both direct image and reflected image by a mirror were analyzed. The accuracy in classifying the maturity of bud varied among the varieties, the smallest for‘Nobless’(1.5%) and the largest for‘Rote Rose’(13.5%). The time required to process a rose averaged 2.06 seconds, equivalent to the capacity of 1,600 roses per hour.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.22 no.1
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• pp.19-31
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• 2018

For the purpose of the basic educated-establishment on the diagnostic methods of "facial color and shape which reflect human's spiritual essence and personality", we study on the diagnostic value and application of the human face. The study's domain is divided the form and color of human face. And the form and color of human face is respectively observed the diagnostic value and contents. The form of human face reflect plenty the information of the mankind, and the observation of the face is applied to the "Physiognomie" refering to the external features of humans. Therefore the diagnosis on the form of human face is the primary factor in the grouping of five-element human, the discrimination of the Sasang constitution, and the classification of Hyunsang type. The color of human face reflect the physical information of internal organs and the pathological change of disease, therefore we examine the region, character and grade of disease by the inspection of complexion including the changes of color and luster of the facial skin. The inspection on the color is also the primary factor in the grouping of five-element human, the classification of Hyunsang and the differentiation of syndromes. The value of the inspection of complexion including the changes of color and form of the face is widely known. In the future, we think, we need to study more about the theory of the diagnostic value and application of the human face.

• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.103-111
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• 2009

This study is to help make-up and coordination for image-making after analysis of facial color and shape of elderly women. The data was analyzed 55-75 years old 212 elderly women's face color and pictures by means of SPSS 12.0 statistics package. On the basis of the colorimetric data on face by Minolta CM2500D, this research considered the analysis of facial color, patternization of facial color and its analysis by age group; for the analysis of facial shape, this research patternized facial shape and analyzed its characteristic using both contour-based facial shape analysis and Kamata facial shape analysis. As for facial color, it was found that the lower age bracket has bright and reddish face, looking fine, while the higher age bracket has a conspicuously yellowish face, looking bad. The community of facial color is classified as 3 types and it was found out that the facial color of the subjects belonging to Type 3, whose L value is the largest, looked the brightest; the face of the subjects belonging to Type 2, whose a value is the largest, was much tinged with red, and the face of the subjects belonging to Type 1, whose b value is the largest were tinged with yellow. According to the analysis of facial shape, there appeared oval & long forms in the classification by contour, while there appeared a lot of downward-directed power and inner-directed power in the classification by Kamata, which is believed to reflect the phenomenon that their chin line becomes roundish and the facial length also tend to be longer due to aging.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.350-357
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• 2021

In the present study, the seed color of 200 common bean genetic resources was analyzed and located on the HTML color chart to classify these resources according to color characteristics. This classification method predicts the components of seed and may serve as a new method for efficiently using secured genetic resources. The imagary data of common bean exhibiting various seed colors were expressed using the HTML color chart. According to the proposed classification method, the seed color was distributed in seven categories: yellow-green, yellow, brown, red, white, gray, and indigo. In addition, the distribution of each seed color was according to its concentration. The distribution by concentration was the highest for red, whereas the distribution of gray and yellow-green was not concentration-dependent. As the dominant pigments based on color distribution, chlorophylls in yellow-green; carotenoids in yellow; and anthocyanins in brown, red, white, gray, and indigo significantly affected seed color. When expressed objectively, seed colors can be applied to the systematic management, breeding, and cultivation of genetic resources and can be useful for marketing or developing products of desired colors. This method can also be applied to other crops.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.32-39
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• 2004

The color-based vision systems have been used to recognize our team robots, the opponent team robots and a ball in the robot soccer system. The color-based vision systems have the difficulty in that they are very sensitive to color variations brought by brightness changes. In this paper, a neural network trained with data obtained from various illumination conditions is used to classify colors in the modified YUV color space for the robot soccer vision system. For this, a new method to measure brightness is proposed by use of a color card. After the neural network is constructed, a look-up-table is generated to replace the neural network in order to reduce the computation time. Experimental results show that the proposed color classification method is robust under illumination variations.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.21-28
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• 2009

Color polarity classification is a process to determine whether the color of text is bright or dark and it is prerequisite task for text extraction. In this paper we propose a color polarity method to extract text region. Based on the observation for the text and background regions, the proposed method uses the ratios of sizes and standard deviations of bright and dark regions. At first, we employ Otsu's method for binarization for gray scale input region. The two largest segments among the bright and the dark regions are selected and the ratio of their sizes is defined as the first measure for color polarity classification. Again, we select the segments that have the smallest standard deviation of the distance from the center among two groups of regions and evaluate the ratio of their standard deviation as the second measure. We use these two ratio features to determine the text color polarity. The proposed method robustly classify color polarity of the text. which has shown by experimental result for the various font and size.

• Proceedings of the Korea Society of Costume Conference
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• 2005.10a
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• pp.218-219
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• 2005