• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.189-196
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• 2013

This paper presents a two-stage approach to detect pedestrians in video sequences taken from a moving vehicle. The first stage is a preprocessing step, in which potential pedestrians are hypothesized. During the preprocessing step, a difference image is constructed using a global motion estimation, vertical and horizontal edge maps are extracted, and the color difference between the road and pedestrians are determined to create candidate regions where pedestrians may be present. The candidate regions are refined further using the vertical edge symmetry features of the pedestrians' legs. In the next stage, each hypothesis is verified using the integral channel features and an AdaBoost classifier. In this stage, a decision is made as to whether or not each candidate region contains a pedestrian. The proposed algorithm was tested on a range of dataset images and showed good performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.45-47
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• 2022

Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.33-42
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• 2003

In this paper, we propose an enhancement of the ultrasonic image for non-destructive inspection of aircraft composite materials. The ultrasonic images are corrupted by a speckle noise which has the characteristic of granular pattern noise and is in all types of coherent imaging systems, the signal independent and multiplicative noise. In this paper, we derive a filter, called the AWLF(Adaptive Window Log Filter), from the nature of the speckle. The filter is made of the MEAN Filter in the edge region and Log Filter in the flat or noise region. To make a distinction between edge and flat region, we calculate the inclination around the local window instead of computing the local statistics of pixels such as local mean ${\bar{M}}$ and standard deviation ${\sigma}_s$. According to the obtained region, edge region is performed by the mean filter and flat region by the Log filter. Performance of the proposed filter is evaluated by the Enhanced Factor$(F_e)$ and the Speckle Index(SI).

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.39-47
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• 2015

The centrality is calculated to describe the importance of a node in a graph and ranking is given according to the centrality for each node. There are many centrality measures and we use degree centrality, closeness centrality, eigenvector centrality, and betweenness centrality. In this paper, we analyze the effect of an additional edge of a graph on centrality and ranking through experimental computations. It is found that the effect of an additional edge on centrality and ranking of the nodes in the graph is different according to the graph structure using PCA. The results can be used for define the graph characteristics.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1075-1084
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• 2022

Internet of Things(IoT) has become a key available technology for efficiently implementing device to device(D2D) services in various domains such as smart home, healthcare, smart city, agriculture, energy, logistics, and transportation. A lightweight publish/subscribe(Pub/Sub) messaging protocol not only establishes data dissemination pattern but also supports connectivity between IoT devices and their applications. Also, a Pub/Sub broker is deployed to facilitate data exchange among IoT devices. A scalable edge-based publish/subscribe (Pub/Sub) broker overlay networks support latency-sensitive IoT applications. In this paper, we design a hypercube grid quorum(HGQ) for distributed Pub/Sub systems based IoT applications. In designing HGQ, the network of hypercube structures suitable for the publish/subscribe model is built in the edge layer, and the proposed HGQ is designed by embedding a mesh overlay network in the hypercube. As their applications, we propose an HGQ-based mechansim for dissemination of the data of sensors or the message/event of IoT devices in IoT environments. The performance of HGQ is evaluated by analytical models. As the results, the latency and load balancing of applications based on the distributed Pub/Sub system using HGQ are improved.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.430-441
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• 2002

Video object segmentation is an important component for object-based video coding scheme such as MPEG-4. In this paper, a robust algorithm for segmentation of moving objects in video sequences and VOP(Video Object Planes) extraction is presented. The points of this paper are detection, of an accurate object boundary by associating moving object edge with spatial object edge and generation of VOP. The algorithm begins with the difference between two successive frames. And after extracting difference image, the accurate moving object edge is produced by using the Canny algorithm and morphological operation. To enhance extracting performance, we app]y the morphological operation to extract more accurate VOP. To be specific, we apply morphological erosion operation to detect only accurate object edges. And moving object edges between two images are generated by adjusting the size of the edges. This paper presents a robust algorithm implementation for fast moving object detection by extracting accurate object boundaries in video sequences.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.273-285
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• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.639-641
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• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.