• Title/Summary/Keyword: 영상강화카메라

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Experimental studies on surface resistance method of levee based on bio-polymer (바이오폴리머 기반 제방 표면 강화 공법에 대한 실험적 연구)

  • Ko, Dongwoo;Kang, Joongu
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.50-50
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    • 2019
  • 최근 국지성 호우 및 하천 제방의 노후화로 인한 제방 붕괴 피해가 빈번히 발생하면서 제방의 안정성 및 표면 보강을 위한 다양한 연구가 시도되고 있다. 본 연구에서는 제방 붕괴에 따른 피해 최소화 및 대책을 수립하기 위한 방법으로 시멘트와 같은 지구온난화를 야기시키는 물질이 아닌 친환경 신소재 바이오폴리머를 흙과 혼합한 재료를 활용하여 제방의 내구성을 강화하기 위한 연구가 수행되고 있다. 이에 안동하천실증연구센터에서는 현장토를 사용하여 높이 1 m, 폭 3 m, 사면경사 1 : 2, 총 길이 5 m 의 중규모 제방모형을 제작하였으며, 공동연구기관인 카이스트에서 개발된 바이오폴리머와 흙을 적정 비율로 혼합한 바이오-소일을 제방 전면에 일정 두께로 피복하여 월류 발생에 따른 제방 안정성 평가 실험을 수행하였다. 1차 실험은 흙 제방 조건이며, 2 3차 실험은 제방 표면에 5 cm 두께로 신소재가 피복된 조건으로 안정된 결과 도출을 위해 반복 실험을 수행하였다. 제방 천단면 및 사면에서의 유속분포를 측정하기 위해 드론 및 비디오카메라를 활용한 LSPIV 기법을 적용하여 실험조건에 따른 표면유속과 월류 흐름이 제방 붕괴에 미치는 영향에 대해 비교분석하였다. 또한 그래픽 소프트웨어를 이용한 픽셀기반 영상분석 기법을 적용하여 시간에 따른 제방사면의 붕괴면적을 산정하여 신소재 피복에 따른 붕괴 지연효과 분석을 통한 신소재 활용 제방의 현장 적용가능성 및 안정성을 평가하였다. 본 연구결과, 흙 제방의 경우 월류 흐름 발생 직후 침식현상이 전개되어 유속분포가 집중되고 있었으며, 이후 발생하는 강한 수직흐름으로 인해 입자추적을 통한 분석이 더 이상 불가능하였다. 신소재 제방의 경우 월류 흐름 발생 직후 침식은 발생하지 않았으며 일정시간동안 유속분포가 유지되었다. 지속적인 월류 흐름으로 인해 제방 끝단에서 침식이 발생하였으며 이때 최대 유속은 3.3 m/s 로 나타났다. 또한 픽셀기반 분석을 통해 30초 단위로 표면손실률을 산정한 결과, 신소재 활용 제방(2, 3차)의 경우 같은 실험조건에도 불구하고 최종 붕괴시간은 약 3배의 차이를 보였으며, 양생 과정에서의 크랙 발생을 최소화한다면 월류 발생 시 상당한 붕괴지연효과가 있는 것으로 판단된다.

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Modernist painting style in Disney animation (디즈니 애니메이션에 나타난 모더니즘 회화스타일 : 색, 형태, 공간을 중심으로)

  • Moon, Jae-Cheol;Kim, Yu-Mi
    • Cartoon and Animation Studies
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    • s.33
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    • pp.31-53
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    • 2013
  • In the early twentieth century, history of animation began by modern artists, they produced various experimental images with the newly invented film and cameras. Artists in the field of movie, photography, paintings and others manipulated images in motion. But as some animated movies won industrial success and popularity, they became the trend but experimental style of early animation preserved by so-called non-mainstreamers or experimental animators, counteracting commercialism. Disney animation also followed the trend by applying realistic Hollywood film style, the worse critics placed a low value on the animation and it tarnished the image, although it was profitable investment from a business standpoint. To make images realistic, they opened a drawing class that animators developed skills to imitate motions and forms from subjects in real life. Also some techniques and gizmos were used to mimic and simulate three dimensional objects and spaces, multiplane camera and compositing 3D CG images with 2D drawings. Moreover, they brought animation stories from fairly tales or folk tales, and Walt's personal interest in live-action movies, they applied Hollywood-film-like narratives and realistic visual, and harsh criticism ensued. On the surface early disney animations' potential seems to be weakened, but in reality it still exists by simplifying and exaggerating forms and color as modern arts. Disney animation employs concepts of the modernism paintings such as simplified shapes and colors to a character design, when their characters are placed together in a scene, that visual elements cause mental reaction. This modification gives a new internal experience to audiences. As conceptual colors in abstract paintings make images appeared to be flat, coloring characters with no shading make them look flat and comparing to them, background images are also appeared to be flat. On top of that, multi-perspective at background images recalls modernist paintings. This essay goes in details with the animation pioneers' works and how Disney animation developed its techniques to emulate real life and analyses color schemes, forms, and spaces in Disney animation compared with modern artists' works, in that the visual language of Disney animation reminds of impression from abstract paintings in the beginning of the twentieth centuries.

Intelligent Video Surveillance Incubating Security Mechanism in Open Cloud Environments (개방형 클라우드 환경의 지능형 영상감시 인큐베이팅 보안 메커니즘 구조)

  • Kim, Jinsu;Park, Namje
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.5
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    • pp.105-116
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    • 2019
  • Most of the public and private buildings in Korea are installing CCTV for crime prevention and follow-up action, insider security, facility safety, and fire prevention, and the number of installations is increasing each year. In the questionnaire conducted on the increasing CCTV, many reactions were positive in terms of the prevention of crime that could occur due to the installation, rather than negative views such as privacy violation caused by CCTV shooting. However, CCTV poses a lot of privacy risks, and when the image data is collected using the cloud, the personal information of the subject can be leaked. InseCam relayed the CCTV surveillance video of each country in real time, including the front camera of the notebook computer, which caused a big issue. In this paper, we introduce a system to prevent leakage of private information and enhance the security of the cloud system by processing the privacy technique on image information about a subject photographed through CCTV.

Improved Performance of Image Semantic Segmentation using NASNet (NASNet을 이용한 이미지 시맨틱 분할 성능 개선)

  • Kim, Hyoung Seok;Yoo, Kee-Youn;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.57 no.2
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    • pp.274-282
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    • 2019
  • In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

Fast Multiple-Image-Based Deblurring Method (다중 영상 기반의 고속 처리용 디블러링 기법)

  • Son, Chang-Hwan;Park, Hyung-Min
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.49-57
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    • 2012
  • This paper presents a fast multiple-image-based deblurring method that decreases the computation loads in the image deblurring, enhancing the sharpness of the textures or edges of the restored images. First, two blurred images with some blurring artifacts and one noisy image including severe noises are consecutively captured under a relatively long and short exposures, respectively. To improve the processing speeds, the captured multiple images are downsampled at the ratio of two, and then a way of estimating the point spread function(PSF) based on the image or edge patches extracted from the whole images, is introduced. The method enables to effectively reduce the computation time taken in the PSF prediction. Next, the texture-enhanced image deblurring method of supplementing the ability of the texture representation degraded by the downsampling of the input images, is developed and then applied. Finally, to get the same image size as the original input images, an upsampling method of utilizing the sharp edges of the captured noisy image is applied. By using the proposed method, the processing times taken in the image deblurring, which is the main obstacle of its application to the digital cameras, can be shortened, while recovering the fine details of the textures or edge components.

3D Histology Using the Synchrotron Radiation Propagation Phase Contrast Cryo-microCT (방사광 전파위상대조 동결미세단층촬영법을 활용한 3차원 조직학)

  • Kim, Ju-Heon;Han, Sung-Mi;Song, Hyun-Ouk;Seo, Youn-Kyung;Moon, Young-Suk;Kim, Hong-Tae
    • Anatomy & Biological Anthropology
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    • v.31 no.4
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    • pp.133-142
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    • 2018
  • 3D histology is a imaging system for the 3D structural information of cells or tissues. The synchrotron radiation propagation phase contrast micro-CT has been used in 3D imaging methods. However, the simple phase contrast micro-CT did not give sufficient micro-structural information when the specimen contains soft elements, as is the case with many biomedical tissue samples. The purpose of this study is to develop a new technique to enhance the phase contrast effect for soft tissue imaging. Experiments were performed at the imaging beam lines of Pohang Accelerator Laboratory (PAL). The biomedical tissue samples under frozen state was mounted on a computer-controlled precision stage and rotated in $0.18^{\circ}$ increments through $180^{\circ}$. An X-ray shadow of a specimen was converted into a visual image on the surface of a CdWO4 scintillator that was magnified using a microscopic objective lens(X5 or X20) before being captured with a digital CCD camera. 3-dimensional volume images of the specimen were obtained by applying a filtered back-projection algorithm to the projection images using a software package OCTOPUS. Surface reconstruction and volume segmentation and rendering were performed were performed using Amira software. In this study, We found that synchrotron phase contrast imaging of frozen tissue samples has higher contrast power for soft tissue than that of non-frozen samples. In conclusion, synchrotron radiation propagation phase contrast cryo-microCT imaging offers a promising tool for non-destructive high resolution 3D histology.

Enhancement of Iris Masking Security using DNN and Blurring (DNN과 블러링을 활용한 홍채 마스킹 보안 강화 기술)

  • Seungmin Baek;Younghae Choi;Chanwoo Hong;Wonhyung Park
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.141-146
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    • 2022
  • The iris, a biometric information, is safe, unique, and reliable, such as fingerprints, and is personal information that can significantly lower the misrecognition rate than other biometric authentication. However, due to the nature of biometric authentication, it is impossible to replace it if it is stolen. There is a case in which an actual iris photo is taken and 3d printed so that the eyes work as if they were in front of the camera. As such, there is a possibility of iris leakage through high-definition images and photos. In this paper, we propose to improve iris masking performance by supplementing iris region masking research based on existing blurring techniques. Based on the results derived in this study, it is expected that it can be used for the security of video conference programs and electronic devices.

Implemantation of Smart Home with Fire Detection and Initial Suppression Function (화재 감지 및 초기진압 기능을 가진 스마트 홈 구현)

  • Yeo, Sang-Sam;Kim, Dong-Hwan;Kim, Yang-u;Park, Rae-chang;Kim, Hyeon-u;Kim, Chan-yeong;Kim, Dong-geun;Yu, Injae
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.439-440
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    • 2022
  • 대부분의 주거환경은 가전제품이나 전등 등을 수동적으로 제어하는 방식이 일반적이다. 본 연구에서는 주거환경을 스마트화함으로써 사용자의 불편함과 번거로움을 줄이고 효율적인 환경관리와 보안을 강화를 할 수 있도록 한다. 본 논문은 아두이노, 여러 센서와 블루투스모듈을 사용하여 집 내부 환경을 자동제어관리하고 사용자가 스마트폰 어플로 집 내부 환경을 파악하고 가전제품을 제어함으로써 편리함을 추구함과 동시에 에너지 절약에 도움이 될 수 있게 한다. 또한 와이파이로 연결된 카메라로 영상을 스트리밍하여 집 내부를 확인하고 대응할 수 있게 하여, 현대인의 집을 스마트하게 관리할 수 있는 "아두이노를 이용한 스마트홈"을 제안한다. 기존의 주거환경과 다르게 집 내부의 환경을 자동제어 및 환경정보를 확인하고 사용자가 직접 가전제품을 제어할 수 있으며, CCTV를 통해 집 내부를 확인 할 수 있도록 한다. 또한 화재가 감지되면 경보와 스프링클러가 작동하여 초기진압을 할 수 있다.

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Machine Vision based Quality Management System for Tele-operated Concrete Surface Grinding Machine (원격조종 콘크리트 표면절삭 장비를 위한 머신비전 기반 품질관리 시스템)

  • Kim, Jeonghwan;Phi, Seung Woo;Seo, Jongwon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.4
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    • pp.1683-1691
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    • 2013
  • Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding highly depend on the skills of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. Also, The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the integrated program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.

Histogram-Based Singular Value Decomposition for Object Identification and Tracking (객체 식별 및 추적을 위한 히스토그램 기반 특이값 분해)

  • Ye-yeon Kang;Jeong-Min Park;HoonJoon Kouh;Kyungyong Chung
    • Journal of Internet Computing and Services
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    • v.24 no.5
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    • pp.29-35
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    • 2023
  • CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.