• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2538-2541
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• 2009

H.264/AVC High 4:4:4 Intra/Predictive profiles supports RGB 4:4:4 sequences for high fidelity video. RGB color planes rather than YCbCr color planes are preferred by high-fidelity video applications such as digital cinema, medical imaging, and UHDTV. Several RGB coding tools have therefore been developed to improve the coding efficiency of RGB video. In this paper, we propose a new method to extract more accurate correlation parameters for inter-plane prediction. We use a searching method to determine the matched macroblock (MB) that has a similar inter-color relation to the current MB. Using this block, we can infer more accurate correlation parameters to predict chroma MB from luma MB. Our proposed inter-plane prediction mode shows an average bits saving of 15.6% and a PSNR increase of 0.99 dB compared with H.264 high4:4:4 intra-profile RGB coding. Furthermore, extensive performance evaluation revealed that our proposed algorithm has better coding efficiency than existing algorithms..

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1258-1268
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• 2004

We propose a new fast, algorithm which is used for detecting frontal face in the frequency domain based on human skin-color using OCT coefficient of dynamic image compression and skin color information. The region where each pixel has a value of skin-color were extracted from U and V value based on DCT coefficient obtained in the process of Image compression using skin-color map in the Y, U, V color space A morphological filter and labeling method are used to eliminate noise in the resulting image We propose the algorithm to detect fastly human face that estimate the directional feature and variance of luminance block of human skin-color Then Extraction of face was completed adaptively on both background have the object analogous to skin-color and background is simple in the proposed algorithm The performance of face detection algorithm is illustrated by some simulation results earned out on various races We confined that a success rate of 94 % was achieved from the experimental results.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.227-239
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• 2014

This paper proposes an enhance prediction for conventional near-lossless coder to effectively lower external memory bandwidth in image processing SoC. First, we utilize an already reconstructed green component as a base of predictor of the other color component because high correlation between RGB color components usually exists. Next, we can improve prediction performance by applying variable block size prediction. Lastly, we use minimum internal memory and improve a temporal prediction performance by using a template dictionary that is sampled in previous frame. Experimental results show that the proposed algorithm shows better performance than the previous works. Natural images have approximately 30% improvement in coding efficiency and CG images have 60% improvement on average.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.7-14
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• 2005

In this paper we proposed the block-based color image segmentation method using the cylindrical metric to solve the problems such as long processing time and over segmentation due to noise and texture properties in the conventional methods. In the proposed method we define the new similarity function and the merge condition between regions to merge initial regions with the same size considering the color and texture properties of chromatic and achromatic regions which is defined according to the HSI color values, and we continue to merge boundary blocks into the adjacent region already segmented to maintain edges until the size of block is one. In the simulation results the proposed method is better than the conventional methods in the evaluation of the segmented regions of texture and edge region, and we found that the processing time is decreased by factor of two in the proposed method.

• Polymer(Korea)
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• v.36 no.1
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• pp.104-110
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• 2012

The dispersion of pigment particles is important because it is capable of increasing the color strength, contrast, and transmittance of color-LCD products. Pigment dispersion properties are very important factors for the quality of LCD color filters. The chemical structure of polymeric dispersants for pigment is important to improve dispersion stability and prevent aggregation or flocculation of pigment in organic or aqueous systems. Polymeric dispersants should contain both anchoring group that interacts with pigment surface and stabilizing group that provides steric stabilization. Moreover, the molecular weight and composition of block copolymer have the an effect on pigment dispersion. In this study, adequate dispersants, block copolymers containing (2-dimethylamino)ethyl methacrylate as anchoring group and oligo(ethylene oxide)methyl ether methacrylate as a stabilizing group were designed and synthesized by atom transfer radical polymerization in order to prepare well-defined structure, molecular weight and composition.

• Journal of the East Asian Society of Dietary Life
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• v.9 no.3
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• pp.370-375
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• 1999

This study was attempted to examine the sensory quality, the degree of gelatinization, color, texture and moisture content of Paeksulgies made with black color rice. The results were as follows: The moisture contents was about 32-36%. L-value on the control group was high, 94.74 and $A_1$, $A_2$, and $C_1$ group were 78.72, 78.58, and 78.43 respectively. As the amount of color rice was increased, L-value on the Paeksulgis was decreased. The gelatinization of Paeksulgis added with color block rice was most increased at C group and D group. In sensory quality. Paeksulgis added with 4-10% block color rice showed the most favorable sensory evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.361-368
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• 2007

In this paper, we propose a smoke detection method which is based on block-wise difference of image frames in video. Our proposed method is composed of three steps which are (a) the detection step of the changed regions against the background, (b) the background update step, and (c) the smoke determination step from the changed regions. We first construct the block mean Image of frames in video. And to extract the changed regions against the background, we use a block-wise difference between background's block mean image and a current input frame's block mean image. After applying projections in block-based difference images, we can determine the changed regions as rectangles using projections of difference images. we propose a update scheme of background's block mean image using the projections. We decide the smoke region using the femoral statistics of the central position and YUV color in the changed region.

• Journal of Digital Contents Society
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• v.1 no.1
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• pp.53-64
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• 2000

This paper is related to color image segmentation scheme which makes it possible to achieve the excellent segmented results by block-based segmentation using Y/C bit-plane summation image. First, normalized chrominance summation image is obtained by normalizing the image which is summed up the absolutes of color-differential values between R, G, B images. Secondly, upper 2 bits of the luminance image and upper 6bits of and the normalized chrominance summation image are bitwise operated by the pixel to generate the Y/C bit-plane summation image. Next, the Y/C bit-plane summation image divided into predetermined block size, is classified into monotone blocks, texture blocks and edge blocks, and then each classified block is merged to the regions including one more blocks in the individual block type, and each region is selectively allocated to unique marker according to predetermined marker allocation rules. Finally, fine segmented results are obtained by applying the watershed algorithm to each pixel in the unmarked blocks. As shown in computer simulation, the main advantage of the proposed method is that it suppresses the over-segmentation in the texture regions and reduces computational load. Furthermore, it is able to apply global parameters to various images with different pixel distribution properties because they are nonsensitive for pixel distribution. Especially, the proposed method offers reasonable segmentation results in edge areas with lower contrast owing to the regional characteristics of the color components reflected in the Y/C bit-plane summation image.

• Journal of Technologic Dentistry
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• v.39 no.3
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• pp.145-152
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• 2017

Purpose: This study sought to identify changes in the mechanical characteristics and color of zirconia according to different sintering temperatures of the substance. Methods: This study processed some specimens of zirconia into those of $8mm(H){\times}10mm(W){\times}50mm(L){\pm}0.1$ each, and sintered them at $1450{\sim}1600^{\circ}C$ on a $50^{\circ}C-interval$ basis in order to examine how their mechanical characteristics and color are changed. Each specimen sintered using the spectral colorimetric apparatus (Easyshade, VITA, Germany) was observed for each of the color change by sintering temperature. Results: When those specimens were sintered at $1450{\sim}1600^{\circ}C$, they were 0% in absorption ratio and porosity, 20% in shrinkage ratio and $6.10g/cm^3$ in specific gravity. Absorption ration, porosity, shrinkage ratio and specific gravity all didn't vary depending on the sintering temperature. The fracture strength of the specimens was highest or 1037MPa at the sintering temperature of $1550^{\circ}C$ and a little lower or 989MPa at that of $1600^{\circ}C$. No variation in L* value was found depending on the sintering temperature of the specimens, while c* value was highest at that of $1450^{\circ}C$. In addition, h* value was highest when the specimens was sintered at $1550^{\circ}C$. Conclusion: This study could determine how zirconia shows changes in mechanical characteristics and color in accordance with different temperatures of its sintering. It is necessary to supplement the physical data of colored transparent zirconia block which is expected to be widely used in clinical practice.