• 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.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.656-659
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• 2012

In general, images captured by the color filter array are compressed after applying demosaicking process. Since this process introduces data redundancy which can reduce coding efficiency, several methods have been proposed to address this problem. While some conventional approachs convert color format to GBR or YUV 4:2:2 format, we propose to use the YCoCg 4:2:2 format to carry out compression. The proposed method shows an average bits reduction of 3.91% and PSNR increase of 0.04dB compared with H.264 YUV 4:2:0 intra-profile prediction method.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.252-259
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• 2007

With the rapid development of multimedia applications and wireless communication networks, consumer demand for video-over-wireless capability on mobile computing systems is growing rapidly. In this regard, this paper introduces YUV-aware instructions that enhance the performance and efficiency in the processing of color image and video. Traditional multimedia extensions (e.g., MMX, SSE, VIS, and AltiVec) depend solely on generic subword parallelism whereas the proposed YUV-aware instructions support parallel operations on two-packed 16-bit YUV (6-bit Y, 5-bits U, V) values in a 32-bit datapath architecture, providing greater concurrency and efficiency for color image and video processing. Moreover, the ability to reduce data format size reduces system cost. Experiment results on a representative dynamically scheduled embedded superscalar processor show that YUV-aware instructions achieve an average speedup of 3.9x over the baseline superscalar performance. This is in contrast to MMX (a representative Intel#s multimedia extension), which achieves a speedup of only 2.1x over the same baseline superscalar processor. In addition, YUV-aware instructions outperform MMX instructions in energy reduction (75.8% reduction with YUV-aware instructions, but only 54.8% reduction with MMX instructions over the baseline).

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.27-35
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• 2010

Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

• Journal of the Korea Computer Industry Society
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• v.3 no.12
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• pp.1765-1774
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• 2002

A face recognition is currently the field which many research have been processed actively. But many problems must be solved the previous problem. First, We must recognize the face of the object taking a location various lighting change and change of the camera into account. In this paper, we proposed that new method to fund feature within fast and correct computation time after scanning PC camera and ID card picture. It converted RGB color space to YUV. A face skin color extracts which equalize a histogram of Y ingredient without the luminance. After, the method use V' ingredient which transformes V ingredient of YUV and then find the face feature. The reult of the experiment shows getting correct input face image from ID Card picture and PC camera.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.109.3-109
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• 2002

1. Introduction 2. Vision system 3. Effect of brightness variations 4. Color classifier using multi-layer neural network 5. Experimental result of color classifier 6. Applications for robot soccer system 7. Conclusion