• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.102-108
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• 2005

CIELAB coordinate is represented by one lightness component and two chromaticity components and similar to human visual system. Visual devices such as computer monitor display images using RGB coordinate. We propose a technique for inserting the watermark of visually recognizable mark into the middle frequency domain of image. RGB coordinate image is transformed into CIELAB coordinate, which include the characteristics of Human vision and then a* component is transformed into DFT(Discrete Fourier transform) transform.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1564-1565
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• 2007

In comparison with CCFL, LED can have more various colours. The research into BLU to raise colour reproducibility is actively proceeding by using RGB LED. On this study, Direct BLU was designed by white LED and RGB LED. According to the result of the experiment, the colour uniformity degree of BLU model using white LED is better than RGB LED BLU. On the other hand, the colour reproducibility of RGB LED BLU is better than white LED. The research showed that the uniformity of white LED is 81.7%and RGB LED is 70.01%.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.159-162
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• 2003

컬러 특징을 나타내는 전형적인 방법으로 RGB 컬러히스토그램이 있다. RGB 컬러 히스토그램은 RGB 컬러 공간을 일련의 bin으로 나누고 각 bin의 컬러 값에 대응하는 영상 픽셀의 빈도 수를 카운트하는 것으로 영상 검색에서 널리 쓰이고 있다. 그러나 RGB 컬러히스토그램은 영상의 미세한 장면 변화에도 크게 달라지기 때문에 검색 결과에 많은 영향을 줄 수 있다. 본 논문에서는 RGB 컬러히스토그램의 이러한 특성을 개선할 수 있는 새로운 컬러 특징 표현 방법을 제안한다. 제안하는 방법은 RGB 컬러 공간으로부터 RG, GB, BR의 세 가지 평면으로 투영시킨 2차원 투영 맵(2D Projection Maps)을 사용한다. 영상 검색에 대한 실험 결과로부터 제안한 2차원 투영 맵이 RGB 컬러히스토그램보다 더 향상된 검색 효율을 나타내었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.872-875
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• 2014

재난방지 및 구호에 사용되는 로봇의 주된 목적은 인간이 직접적인 접근을 할 수 없는 지역을 사전에 탐사하여 인간으로 하여금 올바른 판단을 돕기 위함에 있다. 하지만, 재난 지역에서는 통신장애 문제나, 육안 식별이 불가능한 상황, 원격조정을 통하여 로봇이 업무 수행에 상당한 제약을 받는다. 이 문제를 해결하기 위해 "LED-RGB 칼라센서를 이용한 상호위치 인식 방법연구"[1]을 수행하였으나, RGB의 인식거리가 상당히 짧고, 판단이 모호한 단점이 발생하였다. 따라서 본 연구에서는 이를 개선한 RGB-D센서를 이용하여 RGB의 인식거리를 증가시켰다. 또한 더욱 높은 정확성을 이용하기 위해, Depth를 사용하여 사물들의 특징점들을 랜드마크로 하고 랜드마크로부터의 상대위치를 파악하여 위치를 추정하는 방법을 제안하고자 한다. 마지막으로 상호인식 알고리즘을 이전 방식과 비교하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.248-249
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• 2022

In this paper, we propose a method for classifying and tracking objects based on information of multiple users obtained using RGB-D cameras. The 3D information and color information acquired through the RGB-D camera are acquired and information about each user is stored. We propose a user classification and location tracking algorithm in the entire image by calculating the similarity between users in the current frame and the previous frame through the information on the location and appearance of each user obtained from the entire image.

• Journal of Information Display
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• v.11 no.2
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• pp.45-48
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• 2010

A direct-lit liquid crystal display that does not use color filters is proposed. A backlight unit that employs compartmentalized RGB LED and lenticular-lens arrays is used instead of color filters to direct the RGB LED lights into the RGB subpixels. The color-filterless LED backlight design, simulation, and experiment results are presented.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.76-78
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• 2009

A liquid crystal display that does not use color filters is proposed. A backlight unit that employs compartmentalized RGB LED arrays and a lenticular lens array is used instead of the color filters in order to direct RGB LED lights into the RGB subpixels. A design of color-filterless LED backlight and experimental results are presented.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.61-71
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• 2018

When triangular meshes are generated from the point clouds in global space reconstructed through camera pose estimation against captured RGB-D streams, the quality of the resulting meshes improves as more triangles are hired. However, for 3D reconstructed models beyond some size threshold, they become to suffer from the ugly-looking artefacts due to the insufficient precision of RGB-D sensors as well as significant burdens in memory requirement and rendering cost. In this paper, for the generation of 3D models appropriate for real-time applications, we propose an effective technique that extracts high-quality textures for moderate-sized meshes from the captured colors associated with the reconstructed point sets. In particular, we show that via a simple method based on the mapping between the 3D global space resulting from the camera pose estimation and the 2D texture space, textures can be generated effectively for the 3D models reconstructed from captured RGB-D image streams.

• Korean Journal of Optics and Photonics
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• v.15 no.2
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• pp.183-189
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• 2004

As high quality digital cameras become readily available, digital cameras are being used not only for simple picture recording but also as information storing media in various fields. However, due to the fact that the spectral responses of the camera sensors are different from color matching functions of the CIE standard observer, the color can not be measured using these cameras. This study shows a method for converting camera image to sRGB image, in which color information is preserved. The transfer matrix between camera output signals and CIE stimulus values was determined using a multiple regression method with Macbeth ColorChecker as target colors. The CIE stimulus values for camera output signals can be mapped with a transfer matrix, and these values are converted to sRGB signals. As the result of testing a Kodak DC220 digital camera, the average color difference of Macbeth ColorChecker between true and displayed colors was 2.1 $\Delta$ $E_{ab}$ $^{*}$.$^{*}$.