• Title, Summary, Keyword: RGB

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Driving Current Control for Time-Stable RGB LED Backlighting Using Time-Varying Transform Matrix (시변 변환 행렬을 이용한 시간에 안정된 RGB LED Backlighting 구동 전류 제어)

  • Park, Kee-Hyon;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.4
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    • pp.42-49
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    • 2009
  • This paper proposes a driving current control method for a back light unit (BLU), consisting of red, green, and blue (RGB) light-emitting diodes (LEDs), whereby an RGB optical sensor is used to check the output color stimulus variation to enable a time-stable color stimulus for light emission by the RGB LED BLU. First, to obtain the present color stimulus information of the RGB LED BLU, an RGB to XYZ transform matrix is derived to enable CIEXYZ values to be calculated for the RGB LED BLU from the output values of an RGB optical sensor. The elements of the RGB to XYZ transform matrix are polynomial coefficients resulting from a polynomial regression. Next, to obtain the proper duty control values for the current supplied to the RGB LEDs, an XYZ to Duty transform matrix is derived to calculate the duty control values for the RGB LEDs from the target CIEXYZ values. The data used to derive the XYZ to Duty transform matrix are the CIEXYZ values for the RGB LED BLU estimated from the output values of the RGB optical sensor and corresponding duty control values applied to the RGB LEDs for the present, first preceding, and second preceding sequential check points. With every fixed-interval check of the color stimulus of the RGB LED BLU, the XYZ to Duty transform matrix changes adaptively according to the present lighting condition of the RGB LED BLU, thereby allowing the RGB LED BLU to emit the target color stimulus in a time-stable format regardless of changes in the lighting condition of the RGB LEDs.

Object Detection and Performance Comparison based on RGB image and thermal infrared radiation (RGB 영상과 열 적외선 영상 기반 객체 탐지 알고리즘 수행 및 성능 비교)

  • Kim, Shin;Lee, Yegi;Yoon, Kyoungro;Lim, Hanshin;Lee, Hee Kyoung;Choo, Hyon-gon;Seo, Jeongil
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.176-179
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    • 2020
  • 현재 대부분의 객체 탐지 알고리즘은 RGB 영상을 기반으로 개발되고 있다. 하지만 안개가 끼거나 비가 오는 날 또는 방중에 촬영한 RGB 영상은 흐리거나 잘 보이지 않아 높지 않은 객체 탐지 결과를 보여줄 수 있다. 열 적외선 영상은 열 센서로 인해 만들어지든 영상으로 RGB 영상에 비해 기상조건이나 촬영 시간대에 상관없이 취득 될 수 있다. 본 논문에서는 RGB 영상과 열 적외선 영상을 기반으로 객체 탐지 알고리즘을 수행하고 각 영상에 따른 객체 탐지 성능을 비교한다. 야간에 취득한 RGB 영상과 열 적외선 영상에 객체 탐지를 수행하였으며, 열 적외선 영상 기반 결과가 RGB 영상 기반일 때 보다 더 높은 정확도를 보여주었다. 추가적으로 밤 시간대의 RGB 영상과 열 적외선 영상을 선정하여 객체 탐지 네트워크를 튜닝하였으며, fine-tuned 네트워크를 이용하여 객체 탐지한 실험 결과 역시 열 적외선 영상이 RGB 영상보다 더 높은 객체 탐지 정확도를 보이는 것을 확인할 수 있었다.

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Development Small Size RGB Sensor for Providing Long Detecting Range (원거리 검출범위를 제공하는 소형 RGB 센서 개발)

  • Seo, Jae Yong;Lee, Si Hyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.174-182
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    • 2015
  • In this paper, we developed the small size RGB sensor that recognizes a long distance using a low-cost color sensor. Light receiving portion of the sensor was used as a camera lens for far distance recognition, and illuminating unit was increased the strength of the light by using a high-power white LED and a lens mounted on the reflector. RGB color recognition algorithm consists of the learning process and the realtime recognition process. We obtain a normalized RGB color reference data in the learning process using the specimens painted with target colors, and classifies the three colors using the Mahalanobis distance in recognition process. We apply the developed the RGB color recognition sensor to a prototype of the part classification system and evaluate the performance of its.

Effects of Extracts Derived from Red Ginseng Residue on Antioxidant Activity and Elastase Inhibition (홍삼박추출물의 항산화활성 및 주름개선 효과)

  • Lee, Mi-Yeon;Kim, Bo-Ae;Yang, Jae-Chan
    • Journal of the Korean Applied Science and Technology
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    • v.33 no.4
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    • pp.658-666
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    • 2016
  • We produced the Red ginseng residue water(RGW), ethanol(RGE), 1,3-butylene glycol(RGB) extract from Red ginseng residues, analyzed the components of the extracts by HPLC, and evaluated the cell viability on B16F10, antioxidant and anti-wrinkle effects for application of cosmetics. As a result, RGW, RGE, RGB have various ginsenoside and its content of RGB were higher than RGW, RGE as component analysis by using high performance liquid chromatography(HPLC). RGW showed similar with RGB in cell viability on B16F10 which were higher than RGE. DPPH radical scavenging activity increased according to the RGE>RGB>RGW. SOD-like activity increased according to the RGB>RGE>RGW. Also, elastase inhibition effect increased according to the RGW>RGB>RGE. These results suggested that RGB and RGW may have potential for the application of antioxidant and anti-wrinkle effects for cosmetics.

Performance Analysis of Object Detection Neural Network According to Compression Ratio of RGB and IR Images (RGB와 IR 영상의 압축률에 따른 객체 탐지 신경망 성능 분석)

  • Lee, Yegi;Kim, Shin;Lim, Hanshin;Lee, Hee Kyung;Choo, Hyon-Gon;Seo, Jeongil;Yoon, Kyoungro
    • Journal of Broadcast Engineering
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    • v.26 no.2
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    • pp.155-166
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    • 2021
  • Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.

A Study on the Color Conversion Application of Digital Image in Proof Printer Device (교정 인쇄 장치에서 디지털 이미지의 색변환 적용에 관한 연구)

  • Kim, Joeng-Eun;Cho, Ga-Ram;Koo, Chul-Whoi
    • Journal of the Korean Printing Society
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    • v.27 no.1
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    • pp.29-47
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    • 2009
  • Generally, if RGB image is sent to the printer when we print a digital photograph, the printer will convert RGB to CMYK by the inner built-in drive. Because the difference between color domain of RGB and CMYK will cause that change and difference. The most common way to solve the problem is to convert colors by using ICC profile at RIP software or to adapt automatic color converting from the software of the original printer. So we intended to study show which way is most efficient to the digital output and which color mode device is the best based on the printer's own drive in this paper. we tried to observe and check the extended range of color space such as AdobeRGB as well as CMYK and sRGB. Then we made sure which is the suitable color space. Besides, When we convert RGB mode into CMYK mode by utilizing RIP software and adapt the printer's ICC profile made by our selves, we evaluated the output we get and compared the result with extended RGB image. The results are as follows. In case of RGB mode, the printer requests RGB, and that makes the color space more efficient than CMYK's. Converted to CMYK by utilizing RIP software, the chroma is more linearized than the one produced with its' own driver. Compared with sRGB mode's color gamut, AdobeRGB mode's color gamut and CMYK mode's color, CMYK mode's color gamut is the smallest among 3 of them. CMYK mode's color gamut by utilizing RIP software can be changeable. that can be small and narrow or wide and broad. In other words, the volume of color gamut depends on how CMYK is linearized. The color space of sRGB is more advantageous than the one of AdobeRGB in color-reproduction printed. But in the group $-b^*$, the chroma leaves behind in terms of reproduction, In the group of $-a^*$, the chroma is excellent relatively. Visual evaluation of the image, AdobeRGB image has not many reproduction colors. Specially, according to printers' characteristics, Group B of AdobeRGB and sRGB color space is a long way behind In terms of reproduction but Group Y is excellent relatively.

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An Adaptive Filtering Method for Enhancement of Inter-color Plane Estimation in HEVC RExt RGB Images (HEVC RExt RGB 영상의 색평면 간 예측 향상을 위한 적응적 필터링 기법)

  • Choi, Jangwon;Choe, Yoonsik
    • Journal of Broadcast Engineering
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    • v.18 no.4
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    • pp.647-650
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    • 2013
  • HEVC RExt(High Efficiency Video Coding Range Extension) set a goal to support RGB/YUV 4:2:2 4:4:4 color sampling and over 10 bit-depth images. Unlike the previous 4:2:0 color sampling images, RGB images have the high correlation in inter-color planes. Using this characteristic, some methods which are contributed in JCT-VC standardization meetings estimate the pixel values of inter-color plane. But when we use the estimation of inter-color plane in RGB images, high frequency components of RGB images are caused to reduce the coding efficiency because they usually have the low inter-color plane correlation. Therefore, in this paper, we propose an adaptive low pass filtering method in the inter-color plane estimation. Using this method, we can improve the estimation efficiency of inter-color plane in RGB images. The experimental results with HEVC RExt RGB test sequences show that the proposed method has 0.6% BD(Bjontegaard Distortion)-rate gain and some increased complexity compared to the previous inter-color plane estimation method.

Obstacle Avoidance of Indoor Mobile Robot using RGB-D Image Intensity (RGB-D 이미지 인텐시티를 이용한 실내 모바일 로봇 장애물 회피)

  • Kwon, Ki-Hyeon;Lee, Hyung-Bong
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.10
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    • pp.35-42
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    • 2014
  • It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.

Exploring Optimal Threshold of RGB Pixel Values to Extract Road Features from Google Earth (Google Earth에서 도로 추출을 위한 RGB 화소값 최적구간 추적)

  • Park, Jae-Young;Um, Jung-Sup
    • Journal of Korea Spatial Information System Society
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    • v.12 no.1
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    • pp.66-75
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    • 2010
  • The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.

Smoke Detection Based on RGB-Depth Camera in Interior (RGB-Depth 카메라 기반의 실내 연기검출)

  • Park, Jang-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.2
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    • pp.155-160
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    • 2014
  • In this paper, an algorithm using RGB-depth camera is proposed to detect smoke in interrior. RGB-depth camera, the Kinect provides RGB color image and depth information. The Kinect sensor consists of an infra-red laser emitter, infra-red camera and an RGB camera. A specific pattern of speckles radiated from the laser source is projected onto the scene. This pattern is captured by the infra-red camera and is analyzed to get depth information. The distance of each speckle of the specific pattern is measured and the depth of object is estimated. As the depth of object is highly changed, the depth of object plain can not be determined by the Kinect. The depth of smoke can not be determined too because the density of smoke is changed with constant frequency and intensity of infra-red image is varied between each pixels. In this paper, a smoke detection algorithm using characteristics of the Kinect is proposed. The region that the depth information is not determined sets the candidate region of smoke. If the intensity of the candidate region of color image is larger than a threshold, the region is confirmed as smoke region. As results of simulations, it is shown that the proposed method is effective to detect smoke in interior.