• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1595-1613
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• 2017

The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1371-1378
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• 2017

In this paper, we present an upsampling technique for depth map image using selective bilateral weights and a color weight using laplacian function. These techniques prevent color texture copy problem, which problem appears in existing upsamplers uses bilateral weight. First, we construct a high-resolution image using the bicubic interpolation technique. Next, we detect a color texture region using pixel value differences of depth and color image. If an interpolated pixel belongs to the color texture edge region, we calculate weighting values of spatial and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Otherwise we use color weight instead of depth weight. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3217-3238
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• 2018

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.498-508
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• 2001

In this paper, we propose an efficient coding algorithm for the zoom images to find the optimal depth and texture information. The proposed algorithm is the area-based method consisting of two consecutive steps, i) the depth extraction step and ii) the texture extraction step. The X-Y plane of the object space is divided into triangular patches and the depth value of the node is determined in the first step and then the texture of the each patch is extracted in the second step. In the depth extraction step, the depth of the node is determined by applying the block-based disparity compensation method to the windowed area centered at the node. In the second step, the texture of the triangular patches is extracted from the zoom images by applying the affine transformation based disparity compensation method to the triangular patches with the depth value extracted from the first step. To improve the quality of image, the interpolation is peformed on the object space instead of the interpolation on the image plane.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.533-546
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• 2014

This paper presents a method for a hybrid (color and depth) camera system construction using a photogrammetric technology. A TOF depth camera is efficient since it measures range information of objects in real-time. However, there are some problems of the TOF depth camera such as low resolution and noise due to surface conditions. Therefore, it is essential to not only correct depth noise and distortion but also construct the hybrid camera system providing a high resolution texture map for generating a 3D model using the depth camera. We estimated geometry of the hybrid camera using a traditional relative orientation algorithm and performed texture mapping using backward mapping based on a condition of collinearity. Other algorithm was compared to evaluate performance about the accuracy of a model and texture mapping. The result showed that the proposed method produced the higher model accuracy.

• Journal of the Korean Society of Tobacco Science
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• v.9 no.2
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• pp.49-57
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• 1987

This study had been conducted to determine morphological characteristics of soil in the major districts cultivating flue-cured tobacco plant. Also native soil productivities were measured by means of bioassay planting tobacco plant without fertilizer at 87 selected soils through field experiment. Morphological characteristics of troll affecting the dry weight of tobacco leaves cultivated in the field were investigated Among soil morphological characteristics, topograpy, slope, topsoil depth, soil depth, and soil texture had influenced with high significant on the dry weight of tobacco leaves. For prediction of dry weight (productivity) of tobacco leaves without fertilizer , multiple regression analysis were introduced using soul morphological characteristics. A combination of topography, slope, topsoil depth, and soil texture was very reliable for prediction of productivity. The regression equation was y = -16.88 -14, 34$X_1$ +20.43$X_2$ +50.21$X_3$ -7.54$X_4$ +13.45$X_5$ R = $0.670^{**}$ Where $X_1$ : Topography $X_2$ : Slope $X_3$ : Topsoil Depth $X_4$ : Soil Depth $X_5$ : Soil Texture

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.799-802
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• 2000

There are many methods that extract the depth information based on the blurring ratio for object point in DFD(Depth from Defocus). However, it is often difficult to measure the depth of the object in two-dimensional images that was affected by various elements such as edges, textures, and etc. To solve the problem, new DFD method employing the texture classification with a neural network is proposed. This method extracts the feature of texture from an evaluation window in an image and classifies the texture class. Finally, It allocates the correspondent value for the blurring ratio. The experimental result shows that the method gives more accurate than the previous methods.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.1-6
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• 2015

PURPOSES : Recently, attempts have been made to evaluate tire-pavement noise based on a measure of Mean Profile Depth (MPD). However, equivalent values of MPD appear to correspond to different levels of tire-pavement noise, which indicates that other factors such as texture wavelength need to be included to improve the accuracy of noise prediction. A single index to represent texture wavelength is proposed in this study. A consistent relationship between tire-pavement noise and texture wavelength on asphalt concrete pavement is observed. METHODS : Profile data and tire-pavement noise data were collected from a number of expressway sections in Korea. In addition, texture wavelength was defined by a Peak Number (PN), which was calculated using profile data. Statistical analysis was performed to find the relationship between the PN and tire-pavement noise. RESULTS : As a result of this study, a linear relationship between PN and tire-pavement noise is observed on asphalt concrete pavement. CONCLUSIONS : Tire-pavement noise on asphalt concrete pavement can be predicted from PN information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.551-561
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• 2014

Since the depth and texture images have been widely used for generating 3-dimensional stereoscopic image, the security of them have been focused. In this paper, we propose a new watermarking technique for copyright of stereo and multiview images which is generated in an arbitrary viewpoint by depth and texture image. After the mark space is selected for preserving watermark through DIBR (depth-image-based rendering) process which uses 3D warping, the texture image is transformed to the frequency coefficient using 2D DCT (discrete cosine transform). Some parts of them are quantized, which is the corresponding process to watermarking. The embedded watermark is not conformed by eyes, so we identified the invisibility of the proposed method. In case of appling attacks of general image process, we also identified the robustness of it.

• ETRI Journal
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• v.36 no.2
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• pp.242-252
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• 2014

Since July of 2012, the 3D video extension of H.264/AVC has been under development to support the multi-view video plus depth format. In 3D video applications such as multi-view and free-view point applications, synthesized views are generated using coded texture video and coded depth video. Such synthesized views can be distorted by quantization noise and inaccuracy of 3D wrapping positions, thus it is important to improve their quality where possible. To achieve this, the relationship among the depth video, texture video, and synthesized view is investigated herein. Based on this investigation, an edge noise suppression filtering process to preserve the edges of the depth video and a method based on a total variation approach to maximum a posteriori probability estimates for reducing the quantization noise of the coded texture video. The experiment results show that the proposed methods improve the peak signal-to-noise ratio and visual quality of a synthesized view compared to a synthesized view without post processing methods.