• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.237-237
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• 2012

토파즈는 Al2SiO4 ((F,OH)2) 화학성분을 이루고 있는 광물로써 주로 Fe, Cr, V 등과 같은 불순물을 포함하고 있다. 토파즈는 colorless, blue, pink, yellow 등 다양한 컬러로 산출된다. 결정 내 Si4+ 가 있어야 할 자리에 Al3+ 가 치환되면 Al3+ 를 둘러싸고 있는 4개의 산소 중 하나의 최외각 전자가 전자가를 맞추기 위해 주변에 있던 수소와 결합하여 hole center를 형성한다. 이때 토파즈는 옅은 황색의 컬러를 발색하게 된다. 그 외 청색과 핑크색 등의 컬러는 Al3+ 자리에 치환된 Fe, Cr 등과 같은 불순물에 의해 발색을 일으킨다. 또한 토파즈는 인위적으로 감마선, 전자 빔, 양성자 빔, 중성자 빔을 통해서도 hole center를 형성시켜 컬러를 발색시킬 수 있다고 잘 알려져 있다. 본 연구에서는 총 8개의 무색 토파즈를 이용하여 다양한 조건(energy 및 dose)의 전자 빔 조사를 통해 각 조건 별 컬러변화 및 분광학적 특성변화를 관찰하였다. 모든 시료는 WD-XRF를 통해 정성분석을 하였고, 전자스핀공명(ESR)기기를 통해 전자 빔 조사 전과 후 전자의 스핀 특성 변화를 관찰하였다. 자외선-가시광선 분광분석결과 모든 시료는 전자빔 조사 후 황색과 관련이 있는 450 nm 부근의 파장 영역에서 흡수 peak가 증가하는 것을 확인할 수 있었다. 또한 전자 빔 조사 후 전자스핀공명 분석 결과에서도 Fe3+ 와 관련이 있는 g=3.5~4 영역은 감소하는 반면에 hole center와 관련이 있는 g=2.012 영역이 증가하는 향상을 보였다. 본 연구결과를 통해 우리는 전자 빔 조사 조건에 따라 토파즈의 결정 내부에 미치는 영향 및 컬러 변화와의 상관관계에 대해 확인할 수 있었다.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.639-646
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• 2012

To analyzed the shape of Yellow Dots which appeared on the paper printed HP color laser printer, and analyzed the characteristic of Yellow Dots according to time, month, year and same printers. As a result, documents that printed in same printers had an identical Yellow Dots's shapes according to time, month, year. It was presupposed that was not embedded time and date information in HP Color LaserJet printers against Xerox, and printers which have different serial number had similar shapes but it was not identical Yellow Dots. Finally, it was found to be identical patterns in Yellow Dots of HP Color LaserJet printers used analysis. Depending on the results, it could understand HP's pattern. In the future, it will decipher patterns of Yellow Dots which have other informations to include other printer manufacturer.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.119-126
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• 2005

We propose a new content-based image retrieval using a representative color histogram and directional pattern histogram that is adaptive to the classification characteristics of the image blocks. In the proposed method the color and pattern feature vectors are extracted according to the characteristics o: the block classification after dividing the image into blocks with a fixed size. First, the divided blocks are classified as either luminance or color blocks depending on the saturation of the block. Thereafter, the color feature vectors are extracted by calculating histograms of the block average luminance co-occurrence for the luminance block and the block average colors for the color blocks. In addition, block directional pattern feature vectors are extracted by calculating histograms after performing the directional gradient classification of the luminance. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.809-818
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• 2007

In this thesis, the color information is used to extract the traffic sign territory, and for recognizing the extracted image, it proposes the traffic sign recognition system that applies the error back propagation algorithm. The proposed method analyzes the color of traffic sign to extract and recognize the possible territory of traffic sign. The method of extracting the possible territory is to use the characteristics of YUV, YIQ, and CMYK color space from the RGB color space. Morphology uses the geometric characteristics of traffic sign to make the image segmentation. The recognition of traffic signs can be recognized by using the error back propagation algorithm. As a result of the experiment, the proposed system has proven its outstanding capability in extraction and recognition of candidate territory without the influence of differences in lighting and input image in various sizes.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.364-374
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• 2021

In a fiercely competitive market, brands have become an important foundation for people to choose their products, and brands are also symbols of people's status and strength. Therefore, the importance of brand image design is growing. And color is an expression of emotion and can improve the communication and marketing environment of brand image as an important element of brand image. In this study, Interbrand selected Korea-China TOP 50 brand as a survey target in 2019 and downloaded brand CI from each brand's homepage to data images through Adobe Photoshop program and HSB system, and analyzed the color of the brand. There is no big difference in analyzing the color characteristics of Korean and Chinese brands, and the I.R.I color image scale analysis shows that the overall design of Korean brands is vibrant, elegant and warm to consumers. On the other hand, the overall design of the Chinese brand offers consumers a solemn, modern and sophisticated emotional adjective. Based on the results, this study can provide practical implications for companies to select colors and forms when launching their own brands and developing products.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.805-806
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• 2013

In this paper we propose a study on contents color match between a color monitor and a cyliner screen operating by 3D stereoscopic projector. To match colors we did device characterization and produced compensation data to get into the shader that the contents display by.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.463-467
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• 2004

본 논문에서는 컬러정보를 이용하여 외부 조명의 영향에 대응하면서 얼굴 후보영역을 추출하고, 추출된 후보 영역으로부터 다채널 스킨컬러 모델로 특정 정보를 추출하는 검출 기법을 제시한다. 외부 조명에 민감한 스킨컬러 특성을 고려해 색상정보와 광도를 분리할 수 있는 Y $C_{r}$ , $C_{b}$ 색상모델을 이용하며, Green, Blue 채널의 정보를 Gaussian 확률밀도 모델로부터 $C_{b-}$ $C_{g}$ 의 좁은 범위에 분포되어 있는 스킨컬러 영역 밀도를 모델링한다. 또한 얼굴영역에 Region Restricting과 임계값 반복 알고리즘을 사용하여 눈 영역 검출 과정을 보이고, 실시간 복합 얼굴 검출 시스템 조명방식에 의해 결과를 나타낸다.다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.805-808
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• 2004

본 논문에서는 컬러정보를 이용하여 외부 조명의 영향에 대응하면서 얼굴 후보영역을 추출하고, 추출된 후보 영역으로부터 다채널 스킨컬러 모델로 특정 정보를 추출하는 검출 기법을 제시한다. 외부 조명에 민감한 스킨컬러 특성을 고려해 색상정보와 광도를 분리할 수 있는 $YC_rC_b$ 색상모델을 이용하며, Green, Blue 채널의 정보를 Gaussian 확률밀도 모델로부터 $C_b-C_g$의 좁은 범위에 분포되어 있는 스킨컬러 영역 밀도를 모델링한다. 또한 얼굴영역에 Region Restricting과 임계값 반복 알고리즘을 사용하여 눈 영역 검출 과정을 보이고, 실시간 복합 얼굴 검출 시스템 조명방식에 의해 결과를 나타낸다.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.303-311
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• 2011

For us who live in the 21 century, a variety of media and videos such as TV, movies, magazines, internet, etc. have now become indispensable entities. Because of changing age, unlimited sharing of information, and development of machines, fashion and ideas are rapidly conveyed and theres is also a tendency to seek after more sense based and stimulating things. Around us, there are innumerable colors which do not seem to have any special presence like the air and go beyond human ability to identify them. Such colors exert direct influence upon the visual culture and most rapidly reflect that age's trend. It is precisely from this perspective that the importance of neon colors, which have recently received the spotlight, have emerged in a magnified way. Yet, although much research has been conducted on colors by earlier studies, there has been no research on neon colors and as such, I felt the need for a study of neon colors. The purpose of this study is to recognize the importance and psychology of colors within the visual culture, discover whether there is a correlation between the characteristics of neon colors and the visual culture, and seek ways to demonstrate it by applying it to art education.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.707-714
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• 2019

Recently, as the sensor network technologies and camera technologies develops, there are increasing needs by combining two technologies to effectively observe or monitor the areas that are difficult for people to access by using the visual sensor network. Since the applications using visual sensors take pictures of the outdoor areas, the images may not be well contrasted due to cloudy weather or low-light time periods such as a sunset. In this paper, we first model the color characteristics according to illumination using the characteristics of visual sensors that continuously capture the same area. Using this model, a new method for improving low contrast images in real time is proposed. In order to make the model, the regions of interest consisting of the same color are set up and the changes of color according to the brightness of images are measured. The gamma function is used to model color characteristics using the measured data. It is shown by experimental results that the proposed method improves the contrast of an image by adjusting the color components of the low contrast image simply and accurately.