• Title/Summary/Keyword: 영상향상

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What is the reason Chunhyang dances?(II) -An Introduction to the creative way of Korean Ballet by the contrast with Pansori Chunhyang-jeon (왜 춘향은 춤을 추는가(II) - 판소리<춘향전>과의 대비를 통한 한국발레의 창작방안 연구서설)

  • Im, Hyeong-taek
    • (The) Research of the performance art and culture
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    • no.32
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    • pp.305-332
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    • 2016
  • This article is the second one of the continuous study that considering 'body' as important and researching bodies as 'literature-media': the phenomena and functions. The present writer first of all have paid attention to the study of the contrast between pansori and ballet to secure definite, historic and theoretical prospect of this continuous study. In the process, the Korean creative ballets based on Korean classic narratives were illuminated as the glocal culture contents. And then the necessity of citing Korean characteristic rhythm and tune was insisted to acquire the true individuality and identity(What is the reason Chunhyang dances?(I)). The solution is jangdan and chang of pansori. This article aimed the supplementation of detailed and actual arguments to strengthen and formulate the opinion. And then this article desired to estimate the way to improvement of Korean creative ballet by properly citing jangdan and chang with the actual application cases of Korean ballets. Until now, at least pansori have gotten a sort of visual effectiveness: simply be seen and heard as unusual constituent. Thus the necessity of pansori to work motions and choreography beyond the simple usages. Also the way to be extended generally through being refined by the partial applications.

Preliminary growth chamber experiments using thermal infrared image to detect crop disease (적외선 촬영 영상 기반의 작물 병해 모니터링 가능성 타진을 위한 실내 감염 실험)

  • Jeong, Hoejeong;Jeong, Rae-Dong;Ryu, Jae-Hyun;Oh, Dohyeok;Choi, Seonwoong;Cho, Jaeil
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.2
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    • pp.111-116
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    • 2019
  • The biotic stress of garlic and tobacco infected by bacteria and virus was evaluated using a thermal imaging camera in a growth chamber. The remote sensing technique using the thermal camera detected that garlic leaf temperature increased when the leaves were infected by bacterial soft rot of garlic. Furthermore, the temperature of leaf was relatively high for the leaves where the colony-forming unit per mL was large. Such temperature patterns were detected for tobacco leaves infected by Cucumber Mosaic Virus using thermal images. In addition, the crop water stress index (CWSI) calculated from leaf temperature also increased for the leaves infected by the virus. The event such that CWSI increased by the infection of the virus occurred before visual disease symptom appeared. Our results suggest that the thermal imaging camera would be useful for the development of crop remote sensing technique, which can be applied to a smart farm.

Low-complexity Local Illuminance Compensation for Bi-prediction mode (양방향 예측 모드를 위한 저복잡도 LIC 방법 연구)

  • Choi, Han Sol;Byeon, Joo Hyung;Bang, Gun;Sim, Dong Gyu
    • Journal of Broadcast Engineering
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    • v.24 no.3
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    • pp.463-471
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    • 2019
  • This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.

Multi-modal Image Processing for Improving Recognition Accuracy of Text Data in Images (이미지 내의 텍스트 데이터 인식 정확도 향상을 위한 멀티 모달 이미지 처리 프로세스)

  • Park, Jungeun;Joo, Gyeongdon;Kim, Chulyun
    • Database Research
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    • v.34 no.3
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    • pp.148-158
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    • 2018
  • The optical character recognition (OCR) is a technique to extract and recognize texts from images. It is an important preprocessing step in data analysis since most actual text information is embedded in images. Many OCR engines have high recognition accuracy for images where texts are clearly separable from background, such as white background and black lettering. However, they have low recognition accuracy for images where texts are not easily separable from complex background. To improve this low accuracy problem with complex images, it is necessary to transform the input image to make texts more noticeable. In this paper, we propose a method to segment an input image into text lines to enable OCR engines to recognize each line more efficiently, and to determine the final output by comparing the recognition rates of CLAHE module and Two-step module which distinguish texts from background regions based on image processing techniques. Through thorough experiments comparing with well-known OCR engines, Tesseract and Abbyy, we show that our proposed method have the best recognition accuracy with complex background images.

Correction Algorithm of Errors by Seagrasses in Coastal Bathymetry Surveying Using Drone and HD Camera (드론과 HD 카메라를 이용한 수심측량시 잘피에 의한 오차제거 알고리즘)

  • Kim, Gyeongyeop;Choi, Gunhwan;Ahn, Kyungmo
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.6
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    • pp.553-560
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    • 2020
  • This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

Saliency Attention Method for Salient Object Detection Based on Deep Learning (딥러닝 기반의 돌출 객체 검출을 위한 Saliency Attention 방법)

  • Kim, Hoi-Jun;Lee, Sang-Hun;Han, Hyun Ho;Kim, Jin-Soo
    • Journal of the Korea Convergence Society
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    • v.11 no.12
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    • pp.39-47
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    • 2020
  • In this paper, we proposed a deep learning-based detection method using Saliency Attention to detect salient objects in images. The salient object detection separates the object where the human eye is focused from the background, and determines the highly relevant part of the image. It is usefully used in various fields such as object tracking, detection, and recognition. Existing deep learning-based methods are mostly Autoencoder structures, and many feature losses occur in encoders that compress and extract features and decoders that decompress and extend the extracted features. These losses cause the salient object area to be lost or detect the background as an object. In the proposed method, Saliency Attention is proposed to reduce the feature loss and suppress the background region in the Autoencoder structure. The influence of the feature values was determined using the ELU activation function, and Attention was performed on the feature values in the normalized negative and positive regions, respectively. Through this Attention method, the background area was suppressed and the projected object area was emphasized. Experimental results showed improved detection results compared to existing deep learning methods.

Design and Implementation of Mobile Medical Information System Based Radio Frequency IDentification (RFID 기반의 모바일 의료정보시스템의 설계 및 구현)

  • Kim, Chang-Soo;Kim, Hwa-Gon
    • Journal of radiological science and technology
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    • v.28 no.4
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    • pp.317-325
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    • 2005
  • The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. That is, with the new guidelines and technology, hospital business escapes simple fee calculation and insurance claim center. Moreover, MIS(Medical Information System), PACS(Picture Archiving and Communications System), OCS(Order Communicating System), EMR(Electronic Medical Record), DSS(Decision Support System) are also developing. Medical Information System is evolved toward integration of medical IT and situation si changing with increasing high speed in the ICT convergence. These changes and development of ubiquitous environment require fundamental change of medical information system. Mobile medical information system refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to Internet whenever and wherever. RFID is one of the technologies for Automatic Identification and Data Capture(AIDC). It is the core technology to implement Automatic processing system. This paper provides a comprehensive basic review of RFID model in Korea and suggests the evolution direction for further advanced RFID application services. In addition, designed and implemented DB server's agent program and Client program of Mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented medical information system that performed patient data based EMR, HIS, PACS DB environments, and so reduced delay time of requisition, medical treatment, lab.

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Image-Based Automatic Bridge Component Classification Using Deep Learning (딥러닝을 활용한 이미지 기반 교량 구성요소 자동분류 네트워크 개발)

  • Cho, Munwon;Lee, Jae Hyuk;Ryu, Young-Moo;Park, Jeongjun;Yoon, Hyungchul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.6
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    • pp.751-760
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    • 2021
  • Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

Evaluating the Efficiency of Personal Information Protection Activities in a Private Company: Using Stochastic Frontier Analysis (개인정보처리자의 개인정보보호 활동 효율성 분석: 확률변경분석을 활용하여)

  • Jang, Chul-Ho;Cha, Yun-Ho;Yang, Hyo-Jin
    • Informatization Policy
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    • v.28 no.4
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    • pp.76-92
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    • 2021
  • The value of personal information is increasing with the digital transformation of the 4th Industrial Revolution. The purpose of this study is to analyze the efficiency of personal information protection efforts of 2,000 private companies. It uses a stochastic frontier approach (SFA), a parametric estimation method that measures the absolute efficiency of protective activities. In particular, the personal information activity index is used as an output variable for efficiency analysis, with the personal information protection budget and number of personnel utilized as input variables. As a result of the analysis, efficiency is found to range from a minimum of 0.466 to a maximum of 0.949, and overall average efficiency is 0.818 (81.8%). The main causes of inefficiency include non-fulfillment of personal information management measures, lack of system for promoting personal information protection education, and non-fulfillment of obligations related to CCTV. Policy support is needed to implement safety measures and perform personal information encryption, especially customized support for small and medium-sized enterprises.

Proposed Application Design for Community-Based Rehabilitation Services Access in Community Care System: Occupation and Activity Based (커뮤니티케어 제도 내 지역사회중심재활 서비스 접근을 위한 애플리케이션 디자인의 제안 : 작업과 활동 중심으로)

  • Bae, Seong-Hwan;Jang, Yeon-Sig;Baek, Ji-Young
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.4
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    • pp.325-335
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    • 2021
  • Chronic diseases have been increasing recently as the average life expectancy of humans has been extended, and this trend has caused problems such as the widespread demand for health and rehabilitation services and rising medical costs. In order to solve this problem, the community-based rehabilitation has been developed and strengthened in Korea and gradually promoted since 2019. It is important to secure access to clients who want to use services to revitalize community-based rehabilitation. So in this study, as part of the community-based rehabilitation, intends to devise smartphone applications designs and develop a prototype to secure access to community-based occupational therapy services based on occupation and activities. For Occupational Therapy Practice Framework (OTPF), International Classification of Functioning, Disability and Health (ICF), and Allen Diagnostic Module-2 (ADM-2) were used to devise and categorize occupation and activity based application content, and link OTPF, ICF, and ADM-2 through prior research analysis and expert meetings. The derived content was visualized through literature review and activity analysis, and was implemented to enable direct playback within the application using the YouTube API, and finally developed a prototype application. The Android Studio 3.5.2 for Windows 64-bit was used to build the application prototype. In further research, converging various digital technologies for user convenience and additionally researching community-based occupational therapy service providers opinions and service user satisfaction will improve accessibility to community-based occupational therapy services for clients who have difficulty occupational performance in the community.