• Smart Media Journal
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• v.12 no.7
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• pp.59-67
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• 2023

Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.

• Journal of Platform Technology
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• v.11 no.4
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• pp.3-12
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• 2023

In the post-COVID era, the importance of quarantine measures is greatly emphasized, and accordingly, research related to the detection of mask wearing conditions and prevention of other infectious diseases using deep learning is being conducted. However, research on the detection and tracking of visitors to cultural facilities to prevent the spread of diseases is equally important, so research on this should be conducted. In this paper, a convolutional neural network-based object detection model is trained through transfer learning using a pre-collected dataset. The weights of the trained detection model are then applied to a multi-object tracking model to monitor visitors. The visitor detection model demonstrates results with a precision of 96.3%, recall of 85.2%, and an F1-score of 90.4%. Quantitative results of the tracking model include a MOTA (Multiple Object Tracking Accuracy) of 65.6%, IDF1 (ID F1 Score) of 68.3%, and HOTA (Higher Order Tracking Accuracy) of 57.2%. Furthermore, a qualitative comparison with other multi-object tracking models showcased superior results for the model proposed in this paper. The research of this paper can be applied to the hygiene systems within cultural facilities in the post-COVID era.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.77-82
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• 2023

As the method of collecting and utilizing structured and unstructured data develops due to the influence of the Fourth Industrial Revolution, unwanted personal information data is also being collected and utilized, and hackers are attempting various attacks to steal information. As a result, the importance of information protection has increased, and various protection techniques have emerged, among which many studies have been conducted using decentralized techniques of blockchain and various algorithms to strengthen the security of biometric authentication techniques. This paper proposed a public blockchain biometric authentication system that allows users to protect their data in a safer biometric authentication method in the public blockchain and use it in the blockchain through signature with authenticated information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.104-105
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• 2023

해양 관측과 위성 원격탐사를 이용하여 시공간적으로 다양하게 변하는 생태 어장 환경 및 선박 관련 자료를 획득할 수 있다. 이번 연구의 주요 목적은 야간 불빛 위성 자료를 이용하여 광범위한 해역에 대한 어선의 위치 분포를 파악하는 딥러닝 기반 모델을 제안하는 것이다. 제안한 모델의 정확성을 평가하기 위해 야간 조업 어선의 위치를 포함하고 있는 AIS(Automatic Identification System) 정보와 상호 비교 평가 하였다. 이를 위해, 먼저 AIS 자료를 획득 및 분석하는 방법을 소개한다. 해양안전종합시스템(General Information Center on Maritime Safety & Security, GICOMS)으로부터 제공받은 AIS 자료는 동적정보와 정적정보로 나뉜다. 동적 정보는 일별 자료로 구분되어있으며, 이 정보에는 해상이동업무식별번호(Maritime Mobile Service Identity, MMSI), 선박의 시간, 위도, 경도, 속력(Speed over Ground, SOG), 실침로(Course over Ground, COG), 선수방향(Heading) 등이 포함되어 있다. 정적정보는 1개의 파일로 구성되어 있으며, 선박명, 선종 코드, IMO Number, 호출부호, 제원(DimA, DimB, DimC, Dim D), 홀수, 추정 톤수 등이 포함되어 있다. 이번 연구에서는 선박의 정보에서 어선의 정보를 추출하여 비교 자료로 사용하였으며, 위성 자료는 구름의 영향이 없는 깨끗한 날짜의 영상 자료를 선별하여 사용하였다. 야간 불빛 위성 자료, 구름 정보 등을 이용하여 야간 조업 어선의 불빛을 감지하는 심층신경망(Deep Neural Network; DNN) 기반 모델을 제안하였다. 본 연구의결과는 야간 어선의 분포를 감시하고 한반도 인근 어장을 보호하는데 기여할 것으로 기대된다.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.1-24
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• 2023

At present, domestic archives within the realm of performing arts predominantly focus on recording through videos, yet they often lack comprehensive documentation of crucial production processes and content services. Recognizing the contemporary significance of archival content services, this study analyzes the archival content within the national performing arts archives websites of the United Kingdom and the United States, serving as international benchmarks. The findings extrapolate insights and implications to propose enhancements for the Museum of Performing Arts in the National Theater of Korea. The analysis focused mainly on the missions and visions on the websites, examining 107 contents from the UK National Theater, 27 from the United States, and 9 from Korea. The suggested improvements encompass clarifying target users and execution tasks in the mission and vision statements, fostering expert collaborations, incorporating preview features, curating content with a single theme, and organizing a comprehensive list on the National Theater's YouTube channel.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.829-842
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• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Journal of Yeungnam Medical Science
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• v.16 no.2
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• pp.237-243
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• 1999

We conducted this study to find the optimal correction factor(${\alpha}$) of Lassen's linearization algorithm which has been applied for correction of flow-limited uptake at a high flow range in $^{99m}Tc$ d,l-hexamethylpropy leneamine oxime(HMPAO) and $^{99m}Tc$ ethyl cysteinate dimer(ECD). Ten patients with chronic cerebral infarction were involved in this study. We obtained the corrected $^{99m}Tc$ HMPAO and $^{99m}Tc$-ECD brain SPECT(single photon emission computed tomography) using the algorithm with ${\alpha}$ values that varied from 0.1 to 10 and compared the results with regional cerebral blood flow determined by positron emission tomography (PET-rCBF). The multi-modal volume registration by maximization of mutual information was used for matching between PET-rCBF and SPECT images. The highest correlation coefficient between $^{99m}Tc$-HMPAO and $^{99m}Tc$-ECD brain uptake and PET-rCBF was revealed at ${\alpha}$ 1.4 and 2.1, respectively. We concluded that the ${\alpha}$ values of Lassen's linearization algorithm for $^{99m}Tc$-HMPAO and $^{99m}Tc$-ECD brain SPECT images were 1.4 and 2.1, respectively to indicate cerebral blood flow with comparison of PET-rCBF.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.1-12
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• 2011

There has been the increasing concern with the safety of seven major urban infrastructure such as road, electricity, water supply, sewerage and so on due to urban expansion and new town development. However, high technology development for the common duct which can be an alternative for the safety issue has not been completed due to the law of the national security area. Existing management method of the common duct by people could not respond to the urgent accidents adequately and immediately since it is impossible for us to get access to that in case of fire or gas leak. This study suggests to the method of installing monitoring devices and processing CCTV images with a water supply in a TestLab(a variety of the USN(Ubiquitous Sensor Network) equipment was tested in the TestLab in KICT). The suggested management method of common duct facilities make it possible to do real-time monitoring and prompt access and response to an accident inside the common duct.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.