• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1718-1723
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• 2014

We proposes the method to detect the Hangul and English character region from natural image using structural feature of Hangul and English Characters. First, we extract edge features from natural image, Next, if features are not corresponding to the heuristic rule of character features, extracted features filtered out and select candidates of character region. Next, candidates of Hangul character region are merged into one Hangul character using Hangul character merging algorithm. Finally, we detect the final character region by Hangul character class decision algorithm. English character region detected by edge features of English characters. Experimental result, proposed method could detect a character region effectively in images that contains a complex background and various environments. As a result of the performance evaluation, A proposed method showed advanced results about detection of Hangul and English characters region from natural image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.83-89
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• 2022

Internet of Things technology is rapidly developing due to the recent development of information and communication technology. IoT technology utilizes various sensors to generate unique data from each sensor, enabling diagnosis of system status. However, the equipment management system currently in effect is a post-preservation concept in which administrators must deal with the problem after the problem occurs, which could mean system reliability and availability problems due to system errors, and could result in economic losses due to negative productivity disruptions. Therefore, this study confirmed that edge controller control decision algorithms for more efficient operation of rectifiers in the factory by applying intelligent IoT (AIoT) technology and domain knowledge-based modeling for each sensor data collected based on this, outputting appropriate status messages for each scenario.

• KNOM Review
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• v.23 no.1
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• pp.34-42
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• 2020

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point because it takes for the process to be applied and the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain training data for machine learning model from an Integer Linear Programming (ILP) solution. We use the simulation data to train the machine learning model which predicts the optimal VNF deployment in a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution in a 5-minute future time point.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.471-479
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• 2012

Intra prediction is one of the significant techniques in H.264/AVC reference software; however, it has heavy computational complexity. In order to solve this problem, many fast algorithms have been proposed. In this paper, we propose a fast intra mode decision algorithm which predicts the edge direction of the current block using sub-sampled pixels to reduce high computational complexity of the H.264/AVC encoder. The proposed algorithm shows that it not only improves the coding performance but also reduces the computational complexity of the H.264/AVC encoder compared to previous algorithms. The experimental results show that the proposed algorithm achieves the encoding time reduction of 75.93% on an average with slight peak signal-to-noise ratio (PSNR) drop and bit-rate increment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6C
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• pp.585-593
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• 2007

For the improvement of coding efficiency, the H.264 standard uses new coding tools such as VBS, 1/4-pel accurate ME, multiple references, intra prediction, loop filter, etc. Using these coding tools, H.264 has achieved significant improvements from rate-distortion point of view compared to existing standards. However, the encoder complexity is greatly increased due to these coding tools. We focus on the complexity reduction method of intra-mode decision. Our algorithm first restricts selective prediction modes of Intra4x4 using a simple preprocessing. The prediction modes of Intra4x4 are used for restricting those of the other inter-modes. Simulation results show that the proposed method outperforms other conventional methods and save about 82% of total encoding time.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.69-95
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• 2009

This paper examines the motives for location decisions of startups and dynamics of cluster growth. Because the location decision is intrinsically strategic choice by entrepreneurs, it is an interplay of three critical forces; cost-benefit of the choice, R&D ability of new entrants, and R&D capability of incumbents in clusters. The effect of knowledge spillovers influences the cluster growth like a double-edge sword; both a positive effect of technology learning and a negative effect of knowledge de-learning. Using data on 710 bio-tech venture firms in Korea, this paper tests the hypotheses about the factors influencing the growth of the cluster. The empirical analyses suggested that early entrepreneurial activity in the clustered regions were important, however other factors such as the organizational legacy, internal dynamics inside a cluster, and the existence of cooperation norm in the cluster, affected long term viability of the cluster.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.55-63
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• 2017

One of the purposes of Information Technology (IT) is to support human response to natural and social problems such as natural disasters and spread of disease, and to improve the quality of human life. Recent climate change has happened worldwide, natural disasters threaten the quality of life, and human safety is no longer guaranteed. IT must be able to support tasks related to disaster response, and more importantly, it should be used to predict and minimize future damage. In South Korea, the data related to the damage is checked out by each local government and then federal government aggregates it. This data is included in disaster reports that the federal government discloses by disaster case, but it is difficult to obtain raw data of the damage even for research purposes. In order to obtain data, information extraction may be applied to disaster reports. In the field of information extraction, most of the extraction targets are web documents, commercial reports, SNS text, and so on. There is little research on information extraction for government disaster reports. They are mostly text, but the structure of each sentence is very different from that of news articles and commercial reports. The features of the government disaster report should be carefully considered. In this paper, information extraction method for South Korea government reports in the word format is presented. This method is based on patterns and dictionaries and provides some additional ideas for tokenizing the damage representation of the text. The experiment result is F1 score of 80.2 on the test set. This is close to cutting-edge information extraction performance before applying the recent deep learning algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1518-1526
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• 2004

In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.235-242
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• 2004

In this paper, we proposed the algorithm for detection of microtalcification by automatic threshold decision based on region growing method. The region for optimal threshold is grown from local maximum pixel by increasing repeatedly threshold in microralcification candidate region. Then, the optimal threshold is automatically decided at the maximum value of the contrast and edge sharpness in this region. Microcalcifications could be efficiently detected as satisfied result that true positive ratio is 81.5% and average false positive numbers are 1.1 about total 299 microcalcifirations in real image. In a result, we showed that this algorithm can be used to aid diagnostic-radiologist for the diagnosis of the early phase of breast cancer.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.43-46
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• 1990

Modern society is prevailed a lot of allergies. So, the allergy test is very important. There are many kinds of allergy test. A doctor usually uses skin allergy test among many allergy tests. However, little standadization and objectivity of grading-standard has been established in the skin allergy test. A measurement of the reaction area has been a major objective to perform skin allergy test. Recently, a doctor's method is to measure the reaction area after drawing a line that represents the reaction area on the skin. But this method differs slightly from the real reaction area and individual doctor's measurement is different, because the edge of the reaction area is obscure. In this paper, we propose a algorithm which is able to detect vague edges using the fuzzy set. The algorithm that detects the line and curve is proposed first. Here, the maximum value is calculated by comparing the membership function of the line and curve seperately. We also encode the direction of the line and curve by using 8-direction code. Then, we calculate the reaction area by measuring the pixels which are inside the reaction area. And finally the Allergy grade is decided by grading-standard, and we accomplish faster, the 80re accurate and objective allergy grade decision.