• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.541-550
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• 1994

A true color image is needed many data on the occasion of the transmission and storage. Therefore, we want to describe color image by a minority data without unreasonableness at eyesight. In this paper, it is presented 256 colormap construction method in RGB, YIQ/YUV space and common colormap expression method at merge between colormaps by reason of dissimilar original color image to display at a monitor for each other colormap at the same time. In comparison with processed result in RGB, YIQ/YUV space, it was measured by PSNR, standard variation, and edge preservation rate using sobel operator. Process time is 3second in colormap construction and 2second in merge between colormaps. In the PSNR value, RGB space has higher 0.15, 0.34 on an average than YIQ and YUV spae. Standard variation has lower in 0.15, 0.41 on an average than Yiq and YUV space. But in the data compression, YIQ/YUV space have about 1/3 compression efficiency than RGB space by reason of use to only 4bit of 8bit in color component.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.125-132
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• 2006

The existing recognition system of license plates cannot get the satisfactory result in noise environments. The purpose of this paper is to propose an algorithm that can recognize the region of license plates accurately in a noise environment. The algorithm is formulated by reorganizing the U- and V-channels of YUV color space as YUV is insensitive to light and carries less data than RGB color information. The region of license plates has been extracted by the geometric characteristics, sizes, and places of labeling images. The proposed algorithm was found to improve the process of extracting the region of license plates in various noise environments.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.20-25
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• 2019

Most multimedia signals contain image data, so the problem of efficient processing and transmitting the image data is an important task of the information society. This paper proposes a compression algorithm that reduces the color bits according to importance using YUV color space among the various methods of compressing image data. 4: 2: 2 subsampling is the standard in the field of video. Using the color information and the characteristics of the human retina, YUV color data was reduced by 4: 2: 2 subsampling. The YUV images and RGB images can be interconverted using the transformation matrix. The image data was converted into color space by YUV, and the relatively low U and V bits were subjected to a downscaling operation. The data was then compressed through 4: 2: 2 subsampling. The performance of the proposed algorithm was compared and analyzed by a comparison with existing methods. As a result of the analysis, it was possible to compress the image without reducing the information of the low importance color element and without significant deterioration in the quality compared to the original.

• Annual Conference of KIPS
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• 2007.05a
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• pp.305-308
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• 2007

본 논문은 교통표지판을 자동으로 인식하는 방법에 관한 연구로 기존의 교통표지판 인식시스템에서는 인식하는데 걸리는 시간이 길고 잡음환경에서 인식률이 저하되며 변경된 교통표지판은 인식하지 못하는 문제점이 있다. 본 논문에서는 이와 같은 문제점을 해결하기위해 컬러정보를 이용하여 교통표지판 영역을 추출하고 추출된 이미지를 인식하는데 다층퍼셉트론 신경망 알고리즘을 적용하여 교통표지판 인식시스템을 제안한다. 제안된 방법은 교통표지판의 컬러를 분석하여 영상에서 교통표지판 영역을 추출한다. 영역을 추출하는 방법은 RGB 컬러 공간으로부터 YUV, YIQ, CMYK 컬러 공간이 가지는 특성을 이용한다. 형태처리는 교통표지판의 기하학적 특성을 이용하여 군집화한다. 교통표지판 인식은 학습이 가능한 다층퍼셉트론의 오류역전파알고리즘을 적용하여 인식한다. 다층퍼셉트론 신경망 알고리즘은 패턴인식 분야에서 우수한 성능이 입증 되었다.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.563-581
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• 2010

In this paper, we perform subjective visual quality assessments on UHD video for UHD TV services and analyze the assessment results. Demands for video services have been increased with availabilities of DTV, Internet and personal media equipments. With this trend, the demands for high definition video have also been increasing. Currently, 2K-HD ($1920{\times}1080$) video have been widely consumed over DTV, DVD, digital camcoders, security cameras and other multimedia terminals in various types, and recently digital cinema contents of 4K-UHD($3840{\times}2160$) have been popularly produced and the cameras, beam projects, display panels that support for 4K-UHD video start to come out into multimedia markets. Also it is expected that 4K-UHD service will appear soon in broadcasting and telecommunications environments. Therefore, in this paper, subjective assessments of visual quality on resolutions, color formats, frame rates and compression rates have been carried to provide basis information for standardization of signal specification of UHD video and viewing environments for future UHDTV. As the analysis on the assessments, UHD video exhibits better subjective visual quality than HD by the evaluators. Also, the 4K-UHD test sequences in YUV444 shows better subjective visual quality than the 4K-UHD test sequences in YUV422 and YUV420, but there is little perceptual difference on 4K-UHD test sequences between YUV422 and YUV420 formats. For the comparison between different frame rates, 4K-UHD test sequences of 60fps gives better subjective visual quality than those of 30fps. For bit-depth comparison, HD test sequences in 10-bit depth were little differentiated from those in 8-bit depth in subject visual quality assessment. Lastly, the larger the PSNR values of the reconstructed 4K-UHD test sequences are, the higher the subjective visual quality is. Against the viewing distances, the differences among encoded 4K-UHD test sequences were less distinguished in longer distances from the display.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1414-1424
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• 2004

In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.