• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.889-898
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• 1997

Most general content-based image retrieval techniques use color and texture as retrieval indices. Spatial information is not used to color histogram and color pair based on color retrieval techniques. This paper proposes the selection of a set of representative in the duplicated color histogram, the analysis of spatial information of the selected colors and the image retrieval process based on the duplicated color histogram and spatial information. Two color historgrams for background and object are used in order to decide on color selection in the duplicated color histogram. Spatial information is obtained using a maximum entropy discretization. A retrieval process applies to duplicated color histogram and spatial to retrieve input images and relevant images. As the result of experiment of the image retrieval, improved color his togram and spatial information method hs increased the retrieval effectiveness more the color histogram method and color pair method.

• Textile Coloration and Finishing
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• v.17 no.2 s.81
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• pp.19-25
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• 2005

A colour-difference formulae would be based on a colour appearance model, but, So far, most colour-difference formulae in common use are based on empirical fits to data. Therefore, of the many proposed, none are completely satisfactory but advances have been made in recent years. A new color-difference data set has been produced with the aims of making a comparison of the advanced CIE Lab formulae as well as confirming the effect of color-difference. 416 low lightness pairs that have only lightness-difference were produced for evaluation of CIE Lab-based formulae on lightness-difference from glossy polyester fabric. The standard color-difference pair was prepared and used. It was neutral grey sample pair that has only lightness difference. The standard pair was used to investigate lightness tolerances. And grey-scale method used to evaluate visual assessment. CIE Lab coordinates of the samples were measured using a X-Rite 8200 spectrophotometer. Visual assessments were carried out using Gretag Macbeth The Judge II Light Booth. A study of color tolerances at low lightness was carried out and get avaliable some results.

• KSBB Journal
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• v.25 no.5
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• pp.459-465
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• 2010

A simple and efficient analytical method for the simultaneous determination of seven tar color additives was developed using ion pair high performance liquid chromatography. The conditions for HPLC analysis were as follows: column, ${\mu}$-Bondapak C18 (10 ${\mu}m$, 300 ${\times}$ 3.9 mm i.d.); gradient mobile phase, 0.025 mol/L ammonium acetate (containing 0.01 mol/L tetrabutylammonium bromide)-acetonitrile-methanol (65:25:10) as a mobile for fraction A and 0.025 mol/L ammonium acetate (containing 0.01 mol/L tetrabutylammonium bromide)-acetonitrilemethanol (40:50:10) as a mobile for fraction B; flow rate, 1.0 mL/ min; detection wavelength, 254/520/620 nm. We could attain to the detection limits as 0.01~0.05 ${\mu}$g/mL (254 nm) and 0.005~0.01 ${\mu}$g/mL (520 nm) for six red tar color additives, and 0.05 ${\mu}$g/mL (254 nm) and 0.002 ${\mu}$g/mL (620 nm) for Fast green FCF. This analytical method was applicable to determine the tar color additives contained in several commercial cold syrups.

• Textile Coloration and Finishing
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• v.18 no.2 s.87
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• pp.15-23
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• 2006

A new fastness formula based on CIEDE2000 color-difference formula is developed by B. Rigg and his coworkers. It is very simple to calculate fastness grade for color change than ISO 105-A05 fastness formula based on CIELAB color-difference formula. Sample pair sets which cover a wide range color space were accumulated from NCS(Natural Color System) color book. For those sample pair sets, visual measurement experiment and instrument measurement experiment of fastness grade were carried out and each performance of ISO 105-A02 fastness formula and newly developed fastness formula was compared through degree of agreement for visual measurement result. Newly developed fastness formula indicated improved performance for measuring fastness grade but current ISO fastness formula for assessing change in color, ISO 105-A05, was confirmed that it's performance is inadequate to measure fastness grade. Then fastness formulae were examined more closely according to particular color spaces and the correlation of hue, lightness and chrom for measuring fastness grade was also considered in this study.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.2-49
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• 2001

In this paper, a skin-color model in the HSV space was developed. Based on it, face region can be separated from other parts in a image. Face can be detected by the methods of Template and eye-pair. This realized in our robot.

• Textile Coloration and Finishing
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• v.18 no.5 s.90
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• pp.80-87
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• 2006

A new fastness formula based on the CIEDE2000 color-difference formula was developed by B. Rigg and his coworkers. It is much simpler to calculate the staining fastness grade than the ISO 105-A04 fastness formula based on the CIELAB color-difference formula. Sample pair sets, which cover a wide color space range were accumulated from the NCS(Natural Color System) color book. for those sample pair sets, a visual measurement experiment and an instrumental measurement experiment of fastness grade were carried out. Each performance of the ISO 105-A43 fastness formula and newly developed fastness formula was compared through degree of agreement for visual measurement results. The newly developed fastness formula indicated improved performance for measuring fastness grade as it was confirmed that the performance of the current ISO fastness formula ISO 105-A04 for assessing staining, was inadequate for measuring fastness grade. Then the fastness formulae were examined more closely according to the particular color spaces and the correlation of hue, lightness and chroma for measuring staining fastness grade was also considered to recommend more improved fastness formula. By modifying the weighting functions of CIEDE2000, which is a basis of new fastness formula developed by B. Rigg, a modified fastness formula is proposed in this study.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.261-265
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• 2002

The unique colors of paper, that is, blue, green, red, and yellow were used in the estimation of color from the subjective feeling. The monochrome with unique color or the unique color surrounded with the background color was presented. Subject gazed the monochrome or the unique color, which was called target color. The target and background color were the complementary color each other. The various ratios of the area of gazed color and background were taken. Subject answered the level of subjective feeling consisted of pair of adjective items for unique color presented. With the use of the subjective feeling fer the target color presented, the estimation of the unique color was carried out due to Fuzzy theory and neural networks. The results of color difference between unique color presented and the estimated color gave very small value for the case without background, while the results of the case with background color depended on the ratio of area of presented color and background color till the ration of 2:1, The relation showed the Kirschman's law. The color difference saturated in the increase of area of background with the ratio more than 2:1.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.73-78
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• 2002

The unique colors of paper, that is, blue, green, red, and yellow were used in the estimation of color from the subjective feeling. The monochrome with unique color or the unique color surrounded with the background color was presented. subject gazed the monochrome or the unique color, which was tailed target rotor. The target and background color were the complementary color each other. The various ratios of the area of gazed color and background were taken. Subject answered the level of subjective feeling consisted of pair of adjective items for unique color presented. With the use of the subjective feeling for the target color presented, the estimation of the unique color was cai\ulcornerlied out due to Fuzzy theory and neural networks. The results of color difference between unique color presented and the estimated color gave very small value for the case without background, while the results of the case with background color depended on the ratio of area of presented color and background color till the ration of 2:1, The relation showed the Kirschman's law, The color difference saturated In the increase of area of background with the ratio more than 2:1.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.3037-3047
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• 2000

This paper describes a method of tracking a close leading vehicle by color image processing using the pairs of tail and brake lights. which emit red light and are housed on the rear of the vehicle in stop-and-go traffic condition. In the color image converted as an HSV color model. candidate regions of rear lights are identified using the color features of a pair of lights. Then. the pair of tailor brake lights are detected by means of the geometrical features and location features for the pattern of the tail and brake lights. The location of the leading vehicle can be estimated by the location of the detected lights and the vehicle can be tracked continuously. It is also possible to detect the braking status of the leading vehicle by measuring the change in HSV color components of the pair of lights detected. In the experiment. this method tracked a leading vehicle successfully from urban road images and was more useful at night than in the daylight. The KAV-Ill (Korea Autonomous Vehicle- Ill) equipped with a color vision system implementing this algorithm was able to follow a leading vehicle autonomously at speeds of up to 15km!h on a paved road at night. This method might be useful for developing an LSA (Low Speed Automation) system that can relieve driver's stress in the stop-and-go traffic conditions encountered on urban roads.