• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.90-96
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• 2005

This paper develops a multi-casting system could be used in a school and hospital and government and municipal public offices. The developed multi-casting system uses various educational multimedia titles effectively and is capable of remote control by using a network(LAN). The developed system includes speaker control module that make individual or group broadcasting, AV contents control module for using a diverse educational multimedia title effectively and light control module. The system uses RS-485C communication module and the effective control system interface based on GUI.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1347-1355
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• 2019

Deep learning approach based on convolution neural network (CNN) has extensively studied in the field of computer vision. However, periocular feature extraction using CNN was not well studied because it is practically impossible to collect large volume of biometric data. This study uses the ResNet model which was trained with the ImageNet dataset. To overcome the problem of insufficient training data, we focused on the training of multi-layer perception (MLP) having simple structure rather than training the CNN having complex structure. It first extracts features using the pretrained ResNet model and reduces the feature dimension by principle component analysis (PCA), then trains a MLP classifier. Experimental results with the public periocular dataset UBIPr show that the proposed method is effective in person authentication using periocular region. Especially it has the advantage which can be directly applied for other biometric traits.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.227-232
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• 2022

Disasters are now becoming commonplace and especially the vulnerable group such as the disabled, the elderly, children and foreigners are in a state of overlapping disasters. In this situation, ATSC 3.0-based UHDTV disaster information service for the visually and hearing impaired has been developing. This study focuses on the demand data collected through in-depth interview with the impaired. The demand analysis data is very important to development process of technology. The results of the interview show that it is essential to link the UHDTV disaster signals with home-network, IoT, wearable devices, and various assistive devices for the impaired (hearing aid, smart light bulbs, warning light, etc.). In outdoor space, UHDTV disaster information must be connected to public display media, digital signage, kiosk, screens in bus or taxi. If communication aids for the visually and hearing impaired are equipped with a function that can transmit and receive disaster information, it will help to minimize disaster damage.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1166-1174
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• 2017

In general, the detection of the vehicle license plate is a previous step of license plate recognition and has been actively studied for several decades. In this paper, we propose an algorithm to detect a license plate area of a moving vehicle from a video captured by a fixed camera installed on the road using the Convolution Neural Network (CNN) technology. First, license plate images and non-license plate images are applied to a previously learned CNN model (AlexNet) to extract and classify features. Then, after detecting the moving vehicle in the video, CNN detects the license plate area by comparing the features of the license plate region with the features of the license plate area. Experimental result shows relatively good performance in various environments such as incomplete lighting, noise due to rain, and low resolution. In addition, to protect personal information this proposed system can also be used independently to detect the license plate area and hide that area to secure the public's personal information.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.671-680
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• 2014

Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1269-1279
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• 2019

In medical image analysis, segmentation is considered as a vital process since it partitions an image into coherent parts and extracts interesting objects from the image. In this paper, we consider automatic segmentations of OCT retinal images to find six layer boundaries using convolutional neural networks. Segmenting retinal images by layer boundaries is very important in diagnosing and predicting progress of eye diseases including diabetic retinopathy, glaucoma, and AMD (age-related macular degeneration). We applied well-known CNN architecture for general image segmentation, called Segnet, U-net, and CNN-S into this problem. We also proposed a shortest path-based algorithm for finding the layer boundaries from the outputs of Segnet and U-net. We analysed their performance on public OCT image data set. The experimental results show that the Segnet combined with the proposed shortest path-based boundary finding algorithm outperforms other two networks.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.3-13
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• 2021

We propose a moire artifacts removal algorithm for screen-shot images using multiple domain learning. First, we estimate clean preliminary images by exploiting complementary information of the moire artifacts in pixel value and frequency domains. Next, we estimate a clean edge map of the input moire image by developing a clean edge predictor. Then, we refine the pixel and frequency domain outputs to further improve the quality of the results using the estimated edge map as the guide information. Finally, the proposed algorithm obtains the final result by merging the two refined results. Experimental results on a public dataset demonstrate that the proposed algorithm outperforms conventional algorithms in quantitative and qualitative comparison.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1257-1260
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• 2002

3 세대 이동통신 시스템인 UMTS/GPRS 는 모든 MS(Mobile Station)에게 인터넷 서비스를 항상 제공할 수 있도록 하는 것을 목표로 하고 있다. 그러나 최근 인터넷 사용의 증가로 인해 public IPv4 주소 부족 현상이 발생함에 따라 인터넷에 연결되어 있는 모든 MS 에게 public IPv4 주소를 할당하는데 한계가 있다. 이에 따라 3GPP의 Release 2000 IM CN(IP Multimedia Core Network) 서브 시스템에서는 멀티미디어 서비스 지원을 위해 인터넷에 연결되어 있는 모든 MS 에게 IP 를 할당할 수 있도록 IPv6 지원을 필수로 정의하고 있다. 따라서 UMTS/GPRS 에서 IPv6 를 지원할 경우 이동망과 인터넷망간의 패킷 서비스 전달을 위해 게이트웨이 기능을 수행하는 GGSN 에서 가장 큰 변화가 이루어질 것이다. 그러므로 본 논문에서는 GGSN 이 dual stack 을 지원해야하는지에 대해 살펴본 후 UMTS/GPRS 프로토콜 구조를 제안한다. 그리고 IPv6 지원을 위해 GGSN의 기능을 설계하고 GTP 메시지와 IPv6 주소 할당 방법에 대해 살펴본다.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.65-74
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• 2021

Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.64-68
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• 2007

Commercial WiBro and 3G HSDPA services are launched last year in order to provide high speed wireless Internet access and multimedia service. Currently mobile communication service providers concentrate on the deployment of indoor mobile network since indoor traffic is remarkably increased. For fine indoor wireless communication, an installation of access point system via Public IP network which is called Femtocell is required. The development of indoor Femtocell system must be considered in the viewpoint of low hardware complexity, cost reduction, interlocking with WiBro/HSDPA network without change of network component and easy element management. In this paper, we review the implementation issue and technology of dual mode AP which provides WiBro and HSDPA signal to the user simultaneously. Especially, we describe on the HSDPA Femtocell standardization status and possible 3 types of HSDPA communication module development design. Furthermore we analyze the merits and demerits of each HSDPA Femtocell design type and propose a system which enables handover between indoor HSDPA Femtocell and outdoor commercial HSDPA mobile network.