• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.1
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• pp.1-9
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• 2019

In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.

• ETRI Journal
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• v.36 no.3
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• pp.479-489
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• 2014

This paper presents a model-based image steganography method based on Watson's visual model. Model-based steganography assumes a model for cover image statistics. This approach, however, has some weaknesses, including perceptual detectability. We propose to use Watson's visual model to improve perceptual undetectability of model-based steganography. The proposed method prevents visually perceptible changes during embedding. First, the maximum acceptable change in each discrete cosine transform coefficient is extracted based on Watson's visual model. Then, a model is fitted to a low-precision histogram of such coefficients and the message bits are encoded to this model. Finally, the encoded message bits are embedded in those coefficients whose maximum possible changes are visually imperceptible. Experimental results show that changes resulting from the proposed method are perceptually undetectable, whereas model-based steganography retains perceptually detectable changes. This perceptual undetectability is achieved while the perceptual quality - based on the structural similarity measure - and the security - based on two steganalysis methods - do not show any significant changes.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.203-212
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• 2024

Simultaneous motion is essential in the activities of daily living (ADL). For motion intention recognition, surface electromyogram (sEMG) and corresponding motion label is necessary. However, this process is time-consuming and it may increase the burden of the user. Therefore, we propose a simultaneous motion recognition framework using data augmentation based on muscle activation model. The model consists of multiple point sources to be optimized while the number of point sources and their initial parameters are automatically determined. From the experimental results, it is shown that the framework has generated the data which are similar to the real one. This aspect is quantified with the following two metrics: structural similarity index measure (SSIM) and mean squared error (MSE). Furthermore, with k-nearest neighbor (k-NN) or support vector machine (SVM), the classification accuracy is also enhanced with the proposed framework. From these results, it can be concluded that the generalization property of the training data is enhanced and the classification accuracy is increased accordingly. We expect that this framework reduces the burden of the user from the excessive and time-consuming data acquisition.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.317-326
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• 2013

In this paper, we present an effective method for comparing control flow graphs which represent static structures of binary programs. To compare control flow graphs, we measure similarities by comparing instructions and syntactic information contained in basic blocks. In addition, we also consider similarities of edges, which represent control flows between basic blocks, by edge extension. Based on the comparison results of basic blocks and edges, we match most similar basic blocks in two control flow graphs, and then calculate the similarity between control flow graphs. We evaluate the proposed edge extension method in real world Java programs with respect to structural similarities of their control flow graphs. To compare the performance of the proposed method, we also performed experiments with a previous structural comparison for control flow graphs. From the experimental results, the proposed method is evaluated to have enough distinction ability between control flow graphs which have different structural characteristics. Although the method takes more time than previous method, it is evaluated to be more resilient than previous method in comparing control flow graphs which have similar structural characteristics. Control flow graph can be effectively used in program analysis and understanding, and the proposed method is expected to be applied to various areas, such as code optimization, detection of similar code, and detection of code plagiarism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5998-6016
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• 2017

In thin-film transistor liquid-crystal displays (TFT-LCDs), which are most commonly used in mobile devices, the backlight accounts for about 70% of the power consumption. Therefore, most low-power-related studies focus on realizing power savings through backlight dimming. Image compensation is performed to mitigate the visual distortion caused by the backlight dimming. Therefore, popular techniques include pixel compensation for brightness recovery and contrast enhancement, such as histogram equalization. However, existing pixel compensation techniques often have limitations with respect to blur owing to the pixel saturation phenomenon, or because contrast enhancement cannot adequately satisfy the human visual system (HVS). To overcome these, in this study, we propose a novel dimming technique to achieve both power saving and HVS-awareness by combining the pixel compensation and histogram specifications, which convert the original cumulative density function (CDF) by designing and using the desired CDF of an image. Because the process of obtaining the desired CDF is customized to consider image characteristics, histogram specification is found to achieve better HVS-awareness than histogram equalization. For the experiments, we employ the LIVE image database, and we use the structural similarity (SSIM) index to measure the degree of visual satisfaction. The experimental results show that the proposed technique achieves up to 15.9% increase in the SSIM index compared with existing dimming techniques that use pixel compensation and histogram equalization in the case of the same low-power ratio. Further, the results indicate that it achieves improved HVS-awareness and increased power saving concurrently compared with previous techniques.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.768-779
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• 2018

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.37-44
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• 2015

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In our past study, we defined a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also defined a new measure, called the expanded ego betweenness centrality. In this paper, We propose algorithm that quickly computes expanded ego betweenness centrality by exploiting structural properties of expanded ego network. Through the experiment with virtual network used Barab$\acute{a}$si-Albert network model to represent the generic social network and facebook network to represent actual social network, We show that the node's importance rank based on the expanded ego betweenness centrality has high similarity with that the node's importance rank based on the existing betweenness centrality. We also show that the proposed algorithm computes the expanded ego betweenness centrality quickly than existing algorithm.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.126-134
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• 2020

In the case of an earthquake, the fluid storage structure generates hydraulic pressure due to the fluctuation of the fluid. At this time, the hydraulic pressure of the fluid changes not only the peaked acceleration of the earthquake but also the sloshing height of the fluid free water surface. Factors influencing this change in load include the shape of the seismic wave, the maximum seismic strength, the size of the fluid storage structure, the width of the structure, and the height of the fluid. In this study, the effect of the ratio between the height of the fluid and the width of the structure was investigated on the fluctuation characteristics of the fluid. 200mm and 140mm of fluid were placed in a water storage tank with a width of 500mm, and a real seismic wave was applied to measure the shape of the fluctuation of the fluid free water surface. The similarity between the experiment and the analysis was verified through the S.P.H(Smoothed Particle Hydrodynamic) technique, one of the numerical analysis techniques. It was confirmed that the free water surface of the fluid showed a similar shape, through comparison of experiment and analysis. And based on this results, SPH technique was applied to analyze the fluctuation shape of the fluid free water surface while varying the ratio between the fluid height and the structure width. An equation to predict the maximum and minimum heights of the fluid free water surface during an earthquake was proposed, and it was confirmed that the error between the maximum and minimum heights of the fluid free water surface predicted by the proposed equation was within a maximum of 3%.