• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.237-246
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• 2016

DIBR (Depth Image Based Rendering) is a multimedia technology that generates the virtual multi-view images using a color image and a depth image, and it is used for creating glasses-less 3-dimensional display contents. This research describes the effect of depth accuracy about the objective quality of DIBR-based multi-view images. It first evaluated the minimum depth quantization bit that enables the minimum distortion so that people cannot recognize the quality degradation. It then presented the comparative analysis of non-uniform domain-division quantization versus regular linear quantization to find out how effectively express the accuracy of the depth information in same quantization levels according to scene properties.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.137-146
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• 1998

Recently many devices print electronic images in a variety of ways. The reproduced color, however, is different from the original color because of the difference of hardware characteristics. To maintain device independent color, gamut mapping method is proposed. The proposed color gamut mapping uses nonlinear intensity mapping and clipping for saturation mapping on HSI color space. In the dithering operation, expanded nonlinear ordered dithering and modified error diffusion are proposed. The proposed ordered dithering uses expanded nonlinear quantization which considers overlapping phenomena of neighbored printing dots. In the modified error diffusion, quantization errors to be diffused are adjusted to improve both image blur and color change produced in the error diffusion. So, the printed image is similar to the image of monitor. Our results indicate that proposed algorithm can produce high quality image in the low bit color devices.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.100-104
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• 2008

Generally, it is difficult to find constant patterns on identifiers in a container image, since the identifiers are not normalized in color, size, and position, etc. and their shapes are damaged by external environmental factors. This paper distinguishes identifier areas from background noises and removes noises by using an ART2-based quantization method and general morphological information on the identifiers such as color, size, ratio of height to width, and a distance from other identifiers. Individual identifier is extracted by applying the 8-directional contour tracking method to each identifier area. This paper proposes a refined ART2-based RBF network and applies it to the recognition of identifiers. Through experiments with 300 container images, the proposed algorithm showed more improved accuracy of recognizing container identifiers than the others proposed previously, in spite of using shorter training time.

• Journal of IKEEE
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• v.14 no.2
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• pp.76-81
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• 2010

The need for dedicated hardware continue to decrease as the mobile CPU's performance increases. But, there is a limit to a mobile CPU's performance. GP-GPU(General-Purpose computing on Graphics Processing Units) can improve performance without adding other dedicated hardware. This paper presents the implementation of Inverse Quantization, Inverse DCT and Color Space Conversion module in H.264/AVC decoder using GP-GPU for a mobile environments. The proposed architecture improves approximately 40% of performance when it use all the features.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.103-110
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• 2015

Recently, Classification of characters in a 3D FPS game has emerged as a very significant issue. In this study, We propose the game character Classification method using Image Region Segmentation of the extracting meaningful object in a simple operation. In this method, first used a non-linear RGB color model and octree color quantization scheme. The input image represented a less than 20 quantized color and uses a small number of meaningful color histogram. And then, the image divided into small blocks, calculate the degree of similarity between the color histogram intersection and adjacent block in block units. Because, except for the block boundary according to the texture and to extract only the boundaries of the object block. Set a region by these boundary blocks as a game object and can be used for FPS game play. Through experiment, we obtain accuracy of more than 80% for Classification method using each feature. Thus, using this property, characters could be classified effectively and it draws the game more speed and strategic actions as a result.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1668-1675
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• 2008

In this paper, we propose a post-processing technique developed for the subjective improvement of color resolution in DCT-coded color images. The high frequency components caused by complex object parts are compressed and impaired through DCT-based image processing, so color distortions such as blurs in high saturated regions are observed. It's mainly due to the severe loss of color data as Cb and Cr. Generally, the activities of chroma elements in DCT domain correlate strongly with that of luminance as spatial frequency gets higher, and based on the relations between chroma and luma AC activities, we compensate destructed Cb, Cr coefficients using modifications from Y coefficients. Simulation results show that the proposed method enhances color resolution in high saturated region, and improves the visual quality.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1628-1630
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• 1997

The purpose of this study is to see the method of the analysis of EEG(Electroencephalography) whcih is a nonlinear system, to quantize human emotion under color stimulation using the analysis of EEG. The result of this study would be used clinical study and development fo image instruments with color. In this study, the method of the analysis of EEG is power spectrum using FFT(Fast Fourier Transform) and the modelling of EEG under color stimulation base on back propagation Neural Networks ond of AI(Artfical Intellignece) skills. First, input layer make a match to relative power which get analyzing s in 4 channels, and output layer make a match to color stimulation which is measured human emotion. Finally, weights of each neurons determine by learing back porpagation Neural Networks.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.157-160
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• 2000

This paper proposes a color-based image retrieval method using color adjacency and gradient. In proposed method, both the adjacency of different colors and gradient of a color in homogeneous region are considered as features of an image. The gradient, defined as the maximum distance along the direction with largest change of color, is computed for each pixel to determine whether the center color is similar or different to the neighboring colors. Therefore the problems caused by uniform quantization, which is popularly used at most existing retrieval, can be avoided. And furthermore, the storage of the feature is reduced by the proposed binary representation.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.453-456
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• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.