• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.165.1-170
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• 1999

Object segmentation fro natural video scenes has recently become one of very active research to pics due to the object-based video coding standard MPEG-4. Object detection and isolation is also useful for object-based indexing and search of video content, which is a goal of the emerging new standard, MPEG-7. In this paper, an automatic segmentation method of moving objects in image sequence is presented which is applicable to multimedia content authoring for MPEG-4, and two different segmentation approaches suitable for surveillance applications are addressed in raw data domain and compressed bitstream domains. We also propose an object-based video description scheme based on object segmentation for video indexing purposes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.468-471
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• 2004

In this paper, a method for classifying fingerprint ridge lines using runlength codes is proposed. To detect feature points(minutiae) in automatic fingerprint identification system(AFIS), classification of fingerprint ridge lines are essential process. The fingerprint ridge lines are classified by run-length coding, and also the end and bifurcation regions in ridge lines are separated. To evaluate the performance of the proposed method, detected feature regions including minutiae points and classified fingerprint ridge lines are shown.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.186-198
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• 2021

Security control using surveillance cameras is established when people observe all surveillance videos directly. However, this task is labor-intensive and it is difficult to detect all abnormal situations. In this paper, we propose a deep neural network model, called AT-Net, that automatically detects abnormal situations in the surveillance video, and introduces an automatic video surveillance system developed based on this network model. In particular, AT-Net alleviates the ambiguity of existing abnormal situation detection methods by mapping features representing relationships between people and objects in surveillance video to the new tensor structure based on sparse coding. Through experiments on actual surveillance videos, AT-Net achieved an F1-score of about 89%, and improved abnormal situation detection performance by more than 25% compared to existing methods.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.480-488
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• 2022

Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

• ETRI Journal
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• v.46 no.1
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• pp.106-117
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• 2024

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and introduce a new metric, pass-ratio@n, which captures the granularity of accuracy according to the pass rate of test cases. The framework is intended to be fully automatic to handle the repetitive work involved in generating prompts, conducting inferences, and executing the generated codes. A preliminary evaluation focusing on the prompt detail, problem publication date, and difficulty level demonstrates the successful integration of our framework with the LeetCode coding platform and highlights the applicability of the pass-ratio@n metric.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.17-31
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• 2002

The new MPEG-4 video coding standard enables content-based functionalities. Image segmentation is an indispensable process for it. This paper addresses an effective segmentation of non-rigid objects. Non-rigid objects are deformable objects with fuzzy, blurred and indefinite boundaries. So it is difficult to segment deformable objects precisely. In order to solve this problem, we propose an effective segmentation of non-rigid objects using watershed algorithms in still pictures. And we propose an automatic segmentation through intra-frame and inter-frame segmentation process in video sequences. Automatic segmentation preforms boundary-based and region-based segmentation to extract precise object boundaries.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.8
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• pp.768-775
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• 2011

Since error compensation schemes guaranteeing high reliability are required in wireless communication systems for the transmission of the large amount of data, as an efficient error compensation scheme the turbo HARQ scheme combining automatic repeat request and turbo coding has been studied in many places in the literature. In the case of conventional turbo HARQ schemes, the transmitter recognizing NAK signals repetitively sends the whole unit packet to the receiver although the received packet can be partially correctable. Through two successive processes, selection of uncorrectable error data and retransmission of only the relevant parts of the information data, transmission efficiency can be improved. In this paper, we present an error data selection criterion for retransmission using the sign transitions of A Posteriori values and propose a tubo HARQ scheme based on the partial retransmission technique. Through a computer simulation, we show and analyze the performance of the proposed scheme with transmission efficiency.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.552-560
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• 2023

Aircraft midair collisions are dangerous events that can cause massive casualties. To prevent this, civil aviation has mandated the installation of TCAS (ACAS), which is becoming more sophisticated with the help of new technologies. However, there are institutional problems in collecting data for TCAS research in Korea, limiting the ability to obtain data for personal research. ADS-B and Mode-S automatic broadcast various information about the flight status of the aircraft. This data also contains information about TCAS RA, which can be used by anyone to find examples of TCAS RA operation. We used the databases of ADS-B Exchange and Opensky-Network to acquire data and visually represent three TCAS RA cases through Python coding. We also identified domestic TCAS cases in the first half of 2023 and analyzed their characteristics to confirm the usefulness of the data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.11a
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• pp.189-192
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• 2008

Modern broadcasting/multicasting networks has the heterogeneous nature in terms of terminals and available bandwidth. Such heterogeneity could be coped by scalable video coding (SVC) standard developed recently. More specifically, spatial layers of an SVC bitstream can be consumed by different terminals and SNR (and temporal) scalability can be used to cope with bandwidth heterogeneity. In this work, we tackle the problem of SVC adaptation for different user groups receiving the same broadcast/multicast video, so as to provide a flexible tradeoff between the groups while also maximizing the overall quality of the users. The adaptation process to truncate an SVC bitstream is first formulated as an optimization problem. Then the problem is represented by MPEG-21 DIA description tools, which can be solved by a universal processing. The results show that MPEG-21 DIA is useful to enable automatic and interoperable adaptation in our scenario.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.748-766
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• 2013

In this paper, we consider an infrastructure-vehicle-vehicle (I2V2V) based Vehicle Ad-hoc Networks (VANETs), where one base station multicasts data to d vehicular users with the assistance of r vehicular users. A Distributed Luby Transform (DLT) codes based transmission scheme is proposed over lossy VANETs to reduce transmission latency. Furthermore, focusing on the degree distribution of DLT codes, a Modified Deconvolved Soliton Distribution (MDSD) is designed to further reduce the transmission latency and improve the transmission reliability. We investigate the network behavior of the transmission scheme with MDSD, called MDLT based scheme. Closed-form expressions of the transmission latency of the proposed schemes are derived. Performance simulation results show that DLT based scheme can reduce transmission latency significantly compared with traditional Automatic Repeat Request (ARQ) and Luby Transform (LT) codes based schemes. In contrast to DLT based scheme, the MDLT based scheme can further reduce transmission latency and improve FER performance substantially, when both the source-to-relay and relay-to-sink channels are erasure channels.