• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.52-57
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• 2013

This paper describes the color comparison analysis of flame in each standard color model in order to propose the optimal color model for image processing based flame detection algorithm. Histogram intersection values were used to analyze the separation characteristics between color of flame and color of non-flame in each standard color model which are RGB, YCbCr, CIE Lab, HSV. Histogram intersection value in each color model and components is evaluated for objective comparison. The analyzed result shows that YCbCr color model is the most suitable for flame detection by average HI value of 0.0575. Among the 12 components of standard color models, each Cb, R, Cr component has respectively HI value of 0.0433, 0.0526, 0.0567 and they have shown the best flame separation characteristics.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.687-696
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• 2015

JCT-VC (Joint Collaborative Team on Video Coding) continues developing HEVC/Screen Content Coding (HEVC/SCC) as an extension for efficiently coding screen content videos, including computer animations, graphics, and electrical documents, based on HEVC/Range extension (HEVC/RExt.). Color space conversion from RGB space being captured from CCD sensors is popular in natural video coding. However, the conversion is often undesired for screen contents because of a significant loss in perceptual quality. Therefore, several coding tools including cross-component prediction (CCP) and in-loop adaptive color space transform (ACST) have been developed for an efficient screen content video coding in order to reduce the redundancies between color spaces while maintaining the original color space. In this paper, we review the two coding tools, i.e., CCP and ACST exploiting the correlation in the RGB color space and conduct the performance analysis of the coding tools. In our simulation results, CCP and ACST provide 11.7% BD-rate saving and 16.4% BD-rate saving, respectively, while the two coding tools provide 18.2% BD-rate saving in total. Following this idea, if the two coding tools are exclusively selected, we provide 93% encoding measurement time with a 0.3% coding loss.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.129-141
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• 2006

The image data amount is increasing rapidly that used geography, sea information etc. with great development of a remote sensing technology using artificial satellite. Therefore, people need automatic method that use image processing description than macrography for analysis remote sensing image. In this paper, we propose that acquire texture information to use GLCM(Gray Level Co-occurrence Matrix) in red tide area of artificial satellite remote sensing image, and detects red tide area by PCA(principal component analysis) automatically from this data. Method by sea color that one feature of remote sensing image of existent red tide area detection was most. but in this paper, we changed into 2 principal component accumulation images using GLCM's texture feature information 8. Experiment result, 2 principal component accumulation image's variance percentage is 90.4%. We compared with red tide area that use only sea color and It is better result.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1767-1770
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• 2003

This paper proposes an algorithm that can reduce the estimation error of surface spectral-reflectance(SR) when using a conventional 3-band RGB camera. In the proposed method, the estimation error is reduced by using adaptive principle components (PCs) for each color region. To build an adaptive set of PCs, n SR populations are organized for n PC sets using the Lloyd quantizer design algorithm. The Macbeth Color Checker is utilized for the initial representative SR values for 1485 Munsell color chips as the total color population, then the Munsell chips arc divided into subsets with a set of corresponding adaptive PCs organized for each subset.

• Fashion & Textile Research Journal
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• v.4 no.4
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• pp.394-398
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• 2002

The purse of this study was to invesigate the dyeing fastness on extract of bufferbur leaf princeps. The experimental items were divided into the mordant treatment, component of fabric and kind of mordants. The experimental study was done by laundering, abrasion (dry/wet), perspiration (acid/alkali), light, iron fastness test and color difference by C.C.M system. The summerized finding resulted from experiments and investigation are suggested as follows : In the C.C.M test on mordanting method and kind of fabric, color difference of silk was three times higher than cotton. The silk fabric was the highest in simultaneous mordant treatment but cotton fabric was the highest in none mordant. In color difference analysis on 6 mordants, that of silk and cotton was significantly improved when mordants was treatmented. Especially color difference of Fe and Cu mordanting treatment was higher than Cr, Sn, Al and none. In dyeing fastness on mordants laundering, perspiration, abrasion and iron fastness showed 4-5 grade but light-fastness showed 1-3 grade.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.69-72
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• 2002

Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1158-1159
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• 2009

Tri-stimulus values of CIE-XYZ and RGB values obtained by photographic film, CCD camera or scanner depend on the spectral sensitivity of imaging devices and the spectral radiant distribution of the illumination. It is important to record and reproduce the reflectance spectra of the object for true device independent color reproduction and high accurate recording of the scene. In this paper, a method to record the reflection spectra of the object is introduced and its application to spectral endoscopes is presented.

• Textile Coloration and Finishing
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• v.15 no.6
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• pp.47-54
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• 2003

To be dyed with cationic Berberine, the cotton fiber was modified with reactive anionic agent. The Berberine, a natural cationic colorant of pure yellow, is the major component of Amur Cork tree extract and also can be employed as a natural antimicrobial agent due to its characteristic of cationic quaternary ammonium salt. By LC/MS analysis, it became obvious that the Berberine was contained in Amur Cork tree extract as a major color component. The adsorption of the Berberine on the cotton fabrics pretreated with the anionic agent was greatly increased comparing to that of untreated fabric. Because the anionic agent was colorless, it did not cause unintended color change of the dyeings. The dyed fabric with the Berberine has strong antimicrobial activity showing 99.5% of reduction of bacteria against Staphylococcu aureus.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.267-273
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• 2013

We evaluated the morphological characteristics of 79 popcorn inbred lines, which were developed to breeding popcorn variety at Maize Experiment Station, Gangwon Agricultural Research and Extension Services, by examining ten quantitative and three qualitative characteristics. In the survey of 3 qualitative traits for 79 popcorn inbred lines, most inbred lines respectively showed purple (46 inbred lines) at tassel color (QL1), green (55inbred lines) at silk color (QL2) and green (75 inbred lines) at stem color (QL3). While, on the survey of 10 quantitative traits among 79 popcorn inbred lines, they showed the morphological variation in plant height (QN1, $174.2{\pm}34.9$ cm), ear height (QN2, $103.4{\pm}24.7$ cm), ear length (QN3, $9.4{\pm}3.0$ cm), kernel setting length (QN4, $8.4{\pm}2.6$ cm), ear thickness (QN5, $24.9{\pm}7.7$ mm), ear row number (QN6, $14.0{\pm}2.3$ number), ear weight (QN7, $36.5{\pm}26.0$ g), kernel weight (QN8, $30.9{\pm}19.3$ g), 100 kernel weight (QN9, $10.4{\pm}3.8$ g) and germination rate (QN10, $95.3{\pm}8.1%$), respectively. As a result, 5 inbred lines (PS0-001, PS0-003, PS1-002, PS1-003, PS2-009) in the 79 popcorn inbred lines have showed comparatively high values for the five quantitative traits. On the principal component analysis, silk color (QL2), ear length (QN3), kernel setting length (QN4), ear thickness (QN5), ear weight (QN7), kernel weight (QN8) and 100 kernel weight (QN9) greatly contributed in positive direction on the first principal components, whereas tassel color (QL1), stem color (QL3), ear height (QN2) and ear row number (QN6) contributed in negative direction on the first principal component. In addition, plant height (QN1), ear height (QN2), and kernel weight (QN8) contributed in positive direction on the second principal component, and also tassel color (QL1), silk color (QL2), ear length (QN3), ear row number (QN6) and 100 kernel weight (QN9) contributed in negative direction on the second principal component.

• International Journal of Contents
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• v.8 no.1
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.