• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.601-608
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• 2014

In this study we propose an image denoising algorithm appropriate for mobile smart phone equipped with limited computing ability, which has better performance and at the same time comparable quality comparing with previous studies. The proposed image denoising algorithm for mobile smart phone cameras in low level light environment reduces computational complexity and also prevents edge smoothing by extracting just Gaussian noises from the noisy input image. According to the experiment result, we verified that our algorithm has much better PSNR value than methods applying mean filter or median filter. Also the result image from our algorithm has better clear quality since it preserves edges while smoothing input image. Moreover, the suggested algorithm reduces computational complexity about 52% compared to the method applying original Laplacian mask computation, and we verified that our algorithm has good denoising quality by implementing the algorithm in Android smart phone.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.74-82
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• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1254-1259
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• 2010

In this paper, Low Computational Adaptive Expanded Block Search Motion Estimation Method is proposed. Proposed method classifies ME blocks as Average Motion Block(AMB) and Local Motion Block(LMB) according to correlation of reference frame. It could reduce the computational complexity with performing Modified Fast Search(MFS). And accuracy of MV is also increased by 4 sub-blocks on LMB and Block Expansion(BE). The experimental results show that the proposed method has better performance that increased 1.8dB than Diamond Search and 0.6dB than Full Search with 7.5 % computation of Full Search. The proposed method could be applied to video compression and Frame Rate Conversion(FRC).

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.9-18
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• 2020

In the field of image processing, a method of detecting and counting passengers as moving objects when getting on and off the bus has been studied. Among these technologies, one of the artificial intelligence techniques, the deep learning technique is used. As another method, a method of detecting an object using a stereo vision camera is also used. However, these techniques require expensive hardware equipment because of the computational complexity of used to detect objects. However, most video equipments have a significant decrease in computational processing power, and thus, in order to detect passengers on the bus, there is a need for an image processing technology suitable for various equipment using a relatively low computational technique. Therefore, in this paper, we propose a technique that can efficiently obtain the number of passengers on the bus by detecting the contour of the object through the background subtraction suitable for low-cost equipment. Experiments have shown that passengers were counted with approximately 70% accuracy on lower-end machines than those equipped with stereo vision camera.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.41-49
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• 2008

H.264/AVC supports variable block motion compensation, multiple reference images, 1/4-pixel motion vector accuracy, and in-loop deblocking filter, compared with the existing compression technologies. While these coding technologies are major functions of compression rate improvement, they lead to high complexity at the same time. For the H.264 video coding technology to be actually applied on low-end / low-bit rates terminals more extensively, it is essential to improve tile coding speed. Currently the deblocking filter that can improve the moving picture's subjective image quality to a certain degree is used on low-end terminals to a limited extent due to computational complexity. In this paper, a performance improvement method of the deblocking filter that efficiently reduces the blocking artifacts occurred during the compression of low-bit rates digital motion pictures is suggested. In the method proposed in this paper, the image's spatial correlational characteristics are extracted by using the variable block information of motion compensation; the filtering is divided into 4 modes according to the characteristics, and adaptive filtering is executed in the divided regions. The proposed deblocking method reduces the blocking artifacts, prevents excessive blurring effects, and improves the performance about $30{\sim}40%$ compared with the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.432-443
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• 2017

The primary goal of the MPEG-H 3D Audio standard is to provide immersive audio environments for high-resolution broadcasting services such as UHDTV. This standard incorporates a wide range of technologies such as encoding/decoding technology for multi-channel/object/scene-based signal, rendering technology for providing 3D audio in various playback environments, and post-processing technology. The reference software decoder of this standard is a structure combining several modules and can operate in various modes. Each module is composed of independent executable files and executed sequentially, real time decoding is impossible. In this paper, we make DLL library of the core decoder, format converter, object renderer, and binaural renderer of the standard and integrate them to enable frame-based decoding. In addition, by measuring the computation complexity of each mode of the MPEG-H 3D-Audio decoder, this paper also provides a reference for selecting the appropriate decoding mode for various hardware platforms. As a result of the computational complexity measurement, the low complexity profiles included in Korean broadcasting standard has a computation complexity of 2.8 times to 12.4 times that of the QMF synthesis operation in case of rendering as a channel signals, and it has a computation complexity of 4.1 times to 15.3 times of the QMF synthesis operation in case of rendering as a binaural signals.

• Journal of Power Electronics
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• v.19 no.2
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• pp.529-539
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• 2019

The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission systems. To control a MMC system properly, the ac-side current, circulating current and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes advantages of the conventional MPC and has no weighting factors. The cost function and duty cycle are introduced to minimize the tracking error of the ac-side current and to eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to keep the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computational burden. In this paper, a discrete-time mathematical model of a MMC system is developed and the duty ratio of switching state is designed. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.191-202
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• 2021

In an Internet of Things (IoT)-configured system, each device executes on-chip software. Recent IoT devices require fast execution time of complex services, such as analyzing a large amount of data, while maintaining low-power computation. As service complexity increases, the service requires high-performance computing and more space for embedded space. However, the low performance of IoT edge devices and their small memory size can hinder the complex and diverse operations of IoT services. In this paper, we propose a remote on-demand software code execution unit using the cloudification of on-chip code memory to accelerate the program execution of an IoT edge device with a low-performance processor. We propose a simulation approach to distribute remote code executed on the server side and on the edge side according to the program's computational and communicational needs. Our on-demand remote code execution unit simulation platform, which includes an instruction set simulator based on 16-bit ARM Thumb instruction set architecture, successfully emulates the architectural behavior of on-chip flash memory, enabling embedded devices to accelerate and execute software using remote execution code in the IoT environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2930-2947
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• 2014

With the rapid growth of the communication technology, intelligent terminals (i.e. PDAs and smartphones) are widely used in many mobile applications. To provide secure communication in mobile environment, in recent years, many user authentication schemes have been proposed. However, most of these authentication schemes suffer from various attacks and cannot provide provable security. In this paper, we propose a novel remote user mutual authentication scheme for multi-server environments using elliptic curve cryptography (ECC). Unlike other ECC-based schemes, the proposed scheme uses ECC in combination with a secure hash function to protect the secure communication among the users, the servers and the registration center (RC). Through this method, the proposed scheme requires less ECC-based operations than the related schemes, and makes it possible to significantly reduce the computational cost. Security and performance analyses demonstrate that the proposed scheme can solve various types of security problems and can meet the requirements of computational complexity for low-power mobile devices.