• Journal of Korean Ophthalmic Optics Society
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• v.10 no.1
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• pp.1-8
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• 2005

Color vision of color vision deficiency is possible using Color space's conversion of color image. Color vision of the RG-Color vision deficiency is possible by the case to maximize the G channel(+100), the case to minimize the G channel(-100), the case to maximize the R channel(+100), the case to convert the R channel to the yellow(Y) channel that is the value of $(-)b^*$ coordinate in CIE $L^*a^*b^*$ color space, the case to separate with only the B channel and the G channel and to appear by the light and darkness difference again, and the case to receive the image only by the light and darkness after separation of saturation and conversion of RGB channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11C
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• pp.1040-1048
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• 2009

This paper proposes an auto flesh tone balance algorithm for the picture that is taken for people. General white balance algorithms bring neutral region into focus. But, other objects can be basis if its spectral reflectance is known. In this paper the basis for white balance is human face. For experiment, first, transfer characteristic of image sensor is analyzed and camera output RGB on average face chromaticity under standard illumination is calculated. Second, Output rate for the image is adjusted to make RGB rate for the face photo area taken under unknown illumination RGB rate that is already calculated. Input tri-stimulus XYZ can be calculated from camera output RGB by camera transfer matrix. And input tri-stimulus XYZ is transformed to standard color space (sRGB) using sRGB transfer matrix. For display, RGB data is encoded as eight-bit data after gamma correction. Algorithm is applied to average face color that is light skin color of Macbeth color chart and average color of various face colors that are actually measured.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.443-449
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• 2015

In this paper, we proposed Channel allocation scheme according to the user's location with IR. In VLC System, LED can generate various colors of light by controlling the mixing ratio of each individual RGB color element. Thus, each RGB channel will have a different signal power, and each channel will have different performance. This proposed system using Visible light(RGB) as way to transmit signals, it depends on the mixture RGB, which decided the color of light, moreover, each things determined their performance. However, if the signal were fixed allocated RGB to transmit such as the original system, the importance of the each signals a different occur the limit on the quality of signals. To solve this problem in this paper, according to the RGB mixture ratios analyze the performance for the LED, which analyzed based on allocating the signal by transmitting to improve the quality was about how researched. In addition, our proposed system is able to improve the performance of BER and satisfied the Qos to desire users.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.242-243
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• 2011

구조광을 이용하는 깊이 정보 획득 방법에서 코드화된 패턴의 색상 정보는 촬영된 영상으로부터 패턴을 해석하여 패턴의 위상 변화량으로부터 물체의 깊이 정보를 찾기 위함으로 구조광 패턴들이 대상에 정확하게 투영되는 것이 중요하다. 그러나 프로젝터의 특성에 따라 패턴의 RGB 채널들이 종종 좌표에서 어긋나는 현상이 발생하게 된다. 본 논문에서는 프로젝터의 특성에 따른 컬러 구조광의 캘리브레이션을 위한 방법을 제안한다. 제안하는 방법은 시변화 가시구조광 시스템의 캘리브레이션 과정 중에서 투사된 영상으로부터 RGB 패턴 채널을 추출하고, 추출된 패턴으로부터 각 RGB 채널에 대한 히스토그램을 통하여 패턴 채널이 어느 방향으로 번져 나갔는지를 파악하여 원 패턴에 대한 재정렬을 수행한다. 본 논문의 실험결과에 따르면, 기존의 방법에 비해 간단한 방법으로 가시구조광 패턴에 대한 캘리브레션을 수행할 수 있음을 보여준다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1653-1662
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• 2012

Recently, Organic Light Emitting Diode (OLED) that is broadly applied as next generation display has various advantages. However, OLED display causes unbalanced color tone due to the difference of luminance efficiency among luminous elements. In this paper, we propose adaptive color shifter (ACS) to resolve the RGB channel unbalance and to have wide color range of a relatively weak channel using the image processing method. proposed ACS system was simulated using a variety of image. Also, we numerically analyzed using hue histogram, CIE-1931 xyz color space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.492-494
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• 2015

본 논문에서는 철도선상에서 발생할 수 있는 자살 사고를 예방하기 위한 전단계로서 열차의 철도를 추출하는 방법을 제안한다. 본 논문에서 제안된 방법은 철도 영상에서 각각의 RGB 채널 값을 추출한다. 추출된 각각의 RGB 채널 값을 삼각형 타입 의 소속 함수에 적용하여 상한 값과 하한 값을 퍼지 스트레칭 기법으로 철도 영상의 명암 대비를 강조시킨다. 퍼지 스트레칭 기법이 적용된 영상에서 각각의RGB 채널 값을 이용하여 배경을 제거한 후에 그레이 영상으로 변환한다. 변환된 그레이 영상에서 캐니 마스크를 적용하여 철도선의 에지를 검출하고 에지가 검출된 영상에서 허프 변환 기법과 유클리디안 거리를 적용하여 철도를 검출한다. 제안된 방법의 성능을 확인하기 위해서 다양한 각도의 철도 영상을 대상으로 실험한 결과, 제안된 방법이 철도 검출에 가능성 있는 방법인 것을 확인할 수 있었다.

• Journal of IKEEE
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• v.23 no.1
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• pp.44-52
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• 2019

We implement an educational indoor autonomous mobile robot system that integrates LiDAR sensing information with RGB-D camera image information and exploits the integrated information. This system uses the existing sensing method employing a LiDAR with a small number of scan channels to acquire LiDAR sensing information. To remedy the weakness of the existing LiDAR sensing method, we propose the 3D structure recognition technique using depth images from a RGB-D camera and the deep learning based object recognition algorithm and apply the proposed technique to the system.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.167-172
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• 2017

In this paper, we propose a variable RGB interleaving technique for efficient data transmission in LED based visible light communication system. Visible light communication systems that utilize light as a resource for data transmission are affected by the nature of light and the three primary colors of light. However, the nature of light, such as light reflection, diffraction, and superposition, causes interference of the data to be transmitted, causing burst errors in the data. Such a problem causes the BER performance of the visible light communication system to degrade. To solve these problems, this paper attempts to utilize the variable RGB interleaving technique. Through variable RGB interleaving, data burst errors can be reduced and inter channel interference in a visible light communication system can be reduced. In addition, if the proposed system is applied to meet the QoS that depends on the importance of data or the requirements of the user, it can provide QoS requested by the user and enable efficient data transmission.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.46-53
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• 2015

Visible Light Communication (VLC) is effective way to realize the light device and communication device using a Light Emitting Diode (LED) simultaneously. VLC has high security for Field Of View (FOV) communication area, also which is possible to transmit the high data rate using visible light. In VLC, transmitting the divided data by the RGB channels is higher data rate than transmitting the same data by RGB channels. However, it occurred the burst error by scattering and reflection of visible light which is impossible to restore that. To solve the problem, we proposed the 2-step interleaving scheme that high data rate and improve the performance of BER in VLC. The proposed system implements cyclic interleaving and convolutional interleaving that is able to be standardized the performance of RGB channels and improve the performance of BER using error correction.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.