• Journal of Information Display
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• v.1 no.1
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• pp.59-62
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• 2000

The first 9-inch carbon nanotube based color field emission displays (FEDs) are integrated using a paste squeeze technique. The panel is composed of 576 x 242 lines with implementation of low voltage phosphors. The uniform and moving images are achieved only at $2V/{\mu}m$, This demonstrates a turning point of nanotube for large area and full color applications.

• Culinary science and hospitality research
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• v.21 no.2
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• pp.103-118
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• 2015

This study is intended to look into the effect of dining space color and design on customers' psychological response, satisfaction, and reuse intention of restaurants. To achieve this, an empirical survey was carried out based on responses from 400 dining-out customers. The results were as follows. The dining space color and design had a significant and positive effect on customers' psychological reaction, satisfaction and reuse intention of restaurants. This is a result of positively evaluated service through an increased customer emotional response to simultaneous factors. It also suggest a recognition of a customer's psychological response in forming images based on restaurant attributes aside from food quality, such technique, ornamental equipment, sound, and design factors harmonized with indoor environment, in an attempt to increase customer interest in an increasingly competitive business environment. Consequently, dining space color and design can lead to customers' psychological satisfaction and reuse intention.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.778-781
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• 2015

The paper presents a new way of visual descriptor for deformable object retrieval on the basis of partition based description. The proposed descriptor technology partitions a given object into boundary area and interior area and extracts a descriptor from each area. The final descriptor combines these descriptors. From a given image, deformable object is segmented. The center position of the deformable object is calculated. The object is partitioned into N × N blocks on the basis of the given center position. Blocks are classified as boundary area and interior area depending on the pixels in the block. The proposed descriptor consists of extracted MPEG-7 dominant descriptors from both the boundary and interior area. The performance of proposed method is tested on a database of 1,973 handbag images constructed with view point changes. ARR (Average Retrieval Rate) is used for the retrieval accuracy of the proposed algorithm, compared with MPEG-7 dominant color descriptor.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.159-167
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• 2013

In stereo-view system, variations of target camera position or lighting conditions cause discrepancies on the luminance and chrominance components of stereo views. These discrepancies lead to inaccurate frame view prediction and low quality of 3 D video coding. In this paper, an efficient histogram interval calibration method is proposed for stereo-view coding, so as to compensate for the luminance component of target view. First the proposed method is analyzed by the histogram of the target image frame. Then, it divide two sections of histogram of that frame to correct the color discrepancies. Secondly, each section of the target frame is corrected the luminance component by identify the maximum matching region between the reference frame and the target frame. We have verified our proposed histogram matching method in comparison with the other color correction ones. Experimental results show that it can correct better luminance calibration results of PSNR(Peak Signal to Noise Ratio) and has less computation time.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.154-161
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• 2008

In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a fertile. Here we use 10 Kobayashi emotion to represent emotions. - { romantic, clear, natural, casual, elegant chic, dynamic, classic, dandy, modem } The proposed system is composed of feature extraction and classification. To transform the subjective emotions as physical visual features, we extract representative colors and Patterns from textile. Here, the representative color prototypes are extracted by color quantization method, and patterns exacted by wavelet transform followed by statistical analysis. These exacted features are given as input to the neural network (NN)-based classifiers, which decides whether or not a textile had the corresponding emotion. When assessing the effectiveness of the proposed system with 389 textiles collected from various application domains such as interior, fashion, and artificial ones. The results showed that the proposed method has the precision of 100% and the recall of 99%, thereby it can be used in various textile industries.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.147-157
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• 2011

Webcam doesn't perform memory-alignment in order to reduce the transmission time of image data. Memory-unaligned image data is unsuitable for the processing on GPU. Accordingly, we convert it to available color format for optimization in high speed image processing. In this paper, we propose a technique that accelerates webcam's color format conversion by using NVDIA CUDA. We propose an optimization which is about memory accesses and thread composition, also evaluate memory and computing performance for verifying a hypothesis which is the performance of the proposed architecture and optimizing degree on low-performance GPU. Following the optimization technique, we show performance improvements over maximum 68 percent.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1031-1043
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• 2013

Extracting hand region from images is the first part in the process to recognize hand posture and gesture interaction. Therefore, a good segmenting method is important because it determines the overall performance of hand recognition systems. Conventional hand segmentation researches were prone to changing illumination conditions or limited to the ability to detect multiple people. In this paper, we propose a robust technique based on the fusion of skin-color data and depth information for hand segmentation process. The proposed algorithm uses skin-color data to localize accurate seed location for region-growing from a complicated background. Based on the seed location, our algorithm adjusts each detected blob to fill up the hole region. A region-growing algorithm is applied to the adjusted blob boundary at the detected depth image to obtain a robust hand region against illumination effects. Also, the resulting hand region is used to train our skin-model adaptively which further reduces the effects of changing illumination. We conducted experiments to compare our results with conventional techniques which validates the robustness of the proposed algorithm and in addition we show our method works well even in a counter light condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.80-87
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• 2004

In this paper we proposed the novel feature extraction method that is able to extract the individual characters from the license plate area of the car image more precisely by using the RGB color information and the fuzzy binarization newly proposed. The proposed method, first, extracts from the original image the areas that the pixels with the colors around the green are concentrated on as the candidate areas of the license plate, and selects the area with the most intensive distribution of pixels with the white color among the candidate areas as the license plate area. Second the noises of the license plate area should be removed by using 34{\times}$3 Sobel masking, and the fuzzy binarization method are proposed and applied to the license plate area to generate the binarized image of the license plate area. Lastly, the application of the contour tracking algorithm to the binarized area extracts the individual characters from the license plate area. The experiment on a variety of the real car images showed that the proposed method generates the higher rate of success for character extraction than the previous methods.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.280-280
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• 2014

We report the fabrication and electroluminescent characteristics of GaN/InxGa1-xN microdonut-shaped light-emitting diode (LED) microarrays as variable-color emitters. The diameter, width, height, and period of the GaN microdonuts were controlled by their growth parameters and the geometrical factors of the growth mask patterns. For the fabrication of microdonut LEDs, p-GaN/p-AlxGa1-xN/u-GaN/u-InxGa1-xN heteroepitaxial layers were coated on the entire surface of n-GaN microdonuts. The microdonut LED arrays showed strong light emission, which could be seen with the unaided eye under normal room illumination. Additionally, magnified optical images of microdonut LED arrays exhibited microdonut-shaped light emissions having spatially resolved blue and green colors. Their electroluminescence spectra had two dominant peaks at 460 and 560 nm. With increasing applied voltage, the intensity of the blue emission peak increased much faster than that of the green emission peak, indicating that the color of the LEDs is tunable. We also demonstrated that EL spectra of the devices could be controlled by changing the size of microdonut LEDs. What we want to emphasize here with the microdonut LEDs is that they have additional inner sidewall facets which did not exist for other typical three-dimensional structures including nanopyramids and nanorods, and that InxGa1-xN single quantum well formed on the inner sidewall facets had unique thickness and chemical composition, which generated additional EL color. The origin of the electroluminescence peaks was investigated by structural characterizations and chemical analyses.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.801-804
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• 2013

We propose a new tongue examination model according to the taste division of tongue. The proposed sytem consists of image acquisition, region segmentation, color distribution analysis and abnormality decision of tongue. Tongue DB which is classified into abnormality is constructed with tongue images captured from oriental medicine hospital inpatients. We divided 4 basic taste(bitter, sweet, salty and sour) regions and performed color distribution analysis targeting each region under HSI(Hue Saturation Intensity) color model. To minimize the influence of illumination, the histograms of H and S components only except I are utilized. The abnormality of taste regions each by comparing the proposed diagnosis model with diagnosis results by a doctor of oriental medicine. We confirmed the 87.5% of classification results of abnormality by proposed algorithm is coincide with the doctor's results.