• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2073-2078
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• 2016

Recently, there have been many research that recognize the situation using sensors. However, sensor data collection and analysis are still lacking in integration. This is because the data generated by the sensor is difficult to match in terms of metadata and units. Therefore, a methodology for efficiently using data generated from various sensors is needed. In this paper, we propose a system that recognizes the location through information generated from a moving iBeacon. This system constructs the ontology with the data that can recognize the exact position when the patient wearing iBeacon moves in the room. This maps standard items and sensor items, and stores the results of filtering the detected values as knowledge. the system can extract efficient location information by recognizing the value generated by moving the patient carrying iBeacon through the ontology. This can be applied not only to beacons but also to other sensors, and it can be applied variously according to the ontology configuration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.559-560
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• 2017

Recently, as the problem of personal information leakage has emerged, studies on data collection and web document classification have been made. The existing system judges only the existence of personal information, and there is a problem in that unnecessary data is not filtered because classification of documents published by the same name or user is not performed. In this paper, we propose a system that can identify the types of data or homonyms using the crawler and morphological analyzer for solve the problem. The user collects personal information on the web through the crawler. The collected data can be classified through the morpheme analyzer, and then the leaked data can be confirmed. Also, if the system is reused, more accurate results can be obtained. It is expected that users will be provided with customized data.

• Journal of KIISE
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• v.43 no.7
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• pp.773-780
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• 2016

Semantic information and features are very important for Semantic Role Labeling(SRL) though many SRL systems based on machine learning mainly adopt lexical and syntactic features. Previous SRL research based on semantic information is very few because using semantic information is very restricted. We proposed the SRL system which adopts semantic information, such as named entity, word sense disambiguation, filtering adjunct role based on sense, synonym cluster, frame extension based on synonym dictionary and joint rule of syntactic-semantic information, and modified verb-specific numbered roles, etc. According to our experimentations, the proposed present method outperforms those of lexical-syntactic based research works by about 3.77 (Korean Propbank) to 8.05 (Exobrain Corpus) F1-scores.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.246-251
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• 2016

Recently, the influence of SNS and online media is rapidly growing with a consequent increase in the interest of marketing using these tools. Blog marketing can increase the ripple effect and information delivery in marketing at low cost by prioritizing keyword search results of influential portal sites. However, because of the tough competition to gain top ranking of search results of specific keywords, long-term and proactive efforts are needed. Therefore, we propose a new method that recommends associated keyword groups with the possibility of higher exposure of the blog. The proposed method first collects the documents of blog including search results of target keyword, and extracts and filters keyword with higher association considering the frequency and location information of the word. Next, each associated keyword is compared to target keyword, and then associated keyword group with the possibility of higher exposure is recommended considering the information such as their association, search amount of associated keyword per month, the number of blogs including in search result, and average writhing date of blogs. The experiment result shows that the proposed method recommends keyword group with higher association.

• Journal of KIISE
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• v.43 no.7
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• pp.786-794
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• 2016

Recommender systems can be used to assist users in selecting required services for their tasks in Internet of Things (IoT) environments in which diverse services can be provided by utilizing IoT devices. Traditional research on recommendation mainly focuses on predicting preferences of individual users. However, in IoT environments, not only individual users but also groups of users can access services in the environments. In this study, we analyzed user groups' preferences on services and developed service recommendation approach for new groups that do not have a history of accessing IoT-services in a certain place. Our approach extends the traditional user-based collaborative filtering by considering the similarity between user groups based on their member organization. We conducted experiments with a real-world dataset collected from IoT testbed environments. The results demonstrate that the proposed approach is effective to recommend services to new user groups in IoT environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1608-1613
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• 2009

All kinds of equipment which used an embedded system is developed, and these are used as to an actual life in developments regarding an embedded field in a lot of sections. Also, we can collect data from all kinds of sensors through wireless sensor networks, look by real time data collected could be brought if only through embedded system. In this paper we present a plan which improve the capabilities of embedded system only act as a gateway by installing embedded database in an embedded system for the sensing data management that was transmitted by radio from sensor nodes. In other words, by installing an embedded database to store and manage data by sensing data can be reduced the transmission frequency to communicate with a host and by performing the filtering program in embedded system and then by transmitting only valid data to the host can be increase the reliability of the analysis results based on data collected.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.1-7
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• 2005

This paper describes the system for detecting vehicles in the rear and rear-side that access between sidewalk and bus stopped to city road at day by computer vision-based method. This system informs appearance of vehicles to bus driver and passenger for the safety of a bus passenger getting off. The camera mounted on the top portion of the bus exit door gets the rear and rear-side image of the bus whenever a bus stops at the stop. The system sets search area between bus and sidewalk from this image and detects a vehicle by using change of image and sobel filtering in this area. From a central point of the vehicle detected, we can find out the distance, speed and direction by its location, width and length. It alarms the driver and passengers when it's judged that dangerous situation for the passenger getting off happens. This experiment results in a detection rate more than 87% in driving by bus on the road.

• Journal of KIISE:Software and Applications
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• v.32 no.2
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• pp.85-98
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• 2005

Recently, a lot of researches about mobile vision using Personal Digital Assistant(PDA) has been attempted. Many CPUs for PDA are integer CPUs, which have no floating-computation component. It results in slow computation of the algorithms peformed by vision system or image processing, which have much floating-computation. In this paper, in order to resolve this weakness, we propose the Client(PDA)/server(PC) architecture which is connected to each other with a wireless LAN, and we construct the system with pipelining processing using two CPUs of the Client(PDA) and the Server(PC) in image sequence. The Client(PDA) extracts tentative text regions using Edge Density(ED). The Server(PC) uses both the Multi-1.aver Perceptron(MLP)-based texture classifier and Connected Component(CC)-based filtering for a definite text extraction based on the Client(PDA)'s tentativel99-y extracted results. The proposed method leads to not only efficient text extraction by using both the MLP and the CC, but also fast running time using Client(PDA)/server(PC) architecture with the pipelining processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.339-345
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• 2016

In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.