• Title/Summary/Keyword: Image Processing Technology

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Implementation of Intelligent Fire-Detection Systems Using DSP (DSP를 이용한 지능형 화재검출시스템 구현)

  • Kim, Hyun-tae;Song, Chong-kwan;Park, Jang-sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.411-414
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    • 2009
  • Many victims and property damages are caused in fires every year. In this paper, intelligent fire-detection systems with embedded fire-detection algorithms for early fire detection and alarm is proposed to reduce fire damages by using image processing technique, high speed digital signal processor(DSP) technique, and information technique. The fire detection algorithms used for the proposed systems consist of flame and smoke detection algorithms. If flame or smoke is detected respectively, the corresponding alarm signal can be transferred to management computer. And if flame and smoke is detected simultaneously, the fire alarm signal shall be generated. Through several experiments in the physical environment, it is shown that the proposed system works well without malfunction.

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YOLOv5 based Anomaly Detection for Subway Safety Management Using Dilated Convolution

  • Nusrat Jahan Tahira;Ju-Ryong Park;Seung-Jin Lim;Jang-Sik Park
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.2_1
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    • pp.217-223
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    • 2023
  • With the rapid advancement of technologies, need for different research fields where this technology can be used is also increasing. One of the most researched topic in computer vision is object detection, which has widely been implemented in various fields which include healthcare, video surveillance and education. The main goal of object detection is to identify and categorize all the objects in a target environment. Specifically, methods of object detection consist of a variety of significant techniq ues, such as image processing and patterns recognition. Anomaly detection is a part of object detection, anomalies can be found various scenarios for example crowded places such as subway stations. An abnormal event can be assumed as a variation from the conventional scene. Since the abnormal event does not occur frequently, the distribution of normal and abnormal events is thoroughly imbalanced. In terms of public safety, abnormal events should be avoided and therefore immediate action need to be taken. When abnormal events occur in certain places, real time detection is required to prevent and protect the safety of the people. To solve the above problems, we propose a modified YOLOv5 object detection algorithm by implementing dilated convolutional layers which achieved 97% mAP50 compared to other five different models of YOLOv5. In addition to this, we also created a simple mobile application to avail the abnormal event detection on mobile phones.

Binary Classification of Hypertensive Retinopathy Using Deep Dense CNN Learning

  • Mostafa E.A., Ibrahim;Qaisar, Abbas
    • International Journal of Computer Science & Network Security
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    • v.22 no.12
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    • pp.98-106
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    • 2022
  • A condition of the retina known as hypertensive retinopathy (HR) is connected to high blood pressure. The severity and persistence of hypertension are directly correlated with the incidence of HR. To avoid blindness, it is essential to recognize and assess HR as soon as possible. Few computer-aided systems are currently available that can diagnose HR issues. On the other hand, those systems focused on gathering characteristics from a variety of retinopathy-related HR lesions and categorizing them using conventional machine-learning algorithms. Consequently, for limited applications, significant and complicated image processing methods are necessary. As seen in recent similar systems, the preciseness of classification is likewise lacking. To address these issues, a new CAD HR-diagnosis system employing the advanced Deep Dense CNN Learning (DD-CNN) technology is being developed to early identify HR. The HR-diagnosis system utilized a convolutional neural network that was previously trained as a feature extractor. The statistical investigation of more than 1400 retinography images is undertaken to assess the accuracy of the implemented system using several performance metrics such as specificity (SP), sensitivity (SE), area under the receiver operating curve (AUC), and accuracy (ACC). On average, we achieved a SE of 97%, ACC of 98%, SP of 99%, and AUC of 0.98. These results indicate that the proposed DD-CNN classifier is used to diagnose hypertensive retinopathy.

Stress Intensity Factor Measurement of Inclined Crack in Tensile Plates by Use of Photoelasticity (광탄성법을 이용한 인장판의 경사균열 응력확대계수 측정)

  • Baek, Tae-Hyun;Lee, Chun-Tae;Kim, Young-Chul
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.5 no.2
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    • pp.215-222
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    • 2015
  • This paper presents the measurement of stress intensity factors of inclined cracks by use of photoelasticity. The distributions of isochromatics near a crack tip of the specimen loaded by uniaxially tensile load are used for analysis. Accuracy and reliability is enhanced by twice multiplying and sharpening the measured isochromatics using digital image processing. Photoelastic results are compared with those obtained by finite element method. Good agreement between them shows that the photoelastic analysis is reliable.

Object Detection Based on Virtual Humans Learning (가상 휴먼 학습 기반 영상 객체 검출 기법)

  • Lee, JongMin;Jo, Dongsik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.376-378
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    • 2022
  • Artificial intelligence technology is widely used in various fields such as artificial intelligence speakers, artificial intelligence chatbots, and autonomous vehicles. Among these AI application fields, the image processing field shows various uses such as detecting objects or recognizing objects using artificial intelligence. In this paper, data synthesized by a virtual human is used as a method to analyze images taken in a specific space.

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Deep learning approach to generate 3D civil infrastructure models using drone images

  • Kwon, Ji-Hye;Khudoyarov, Shekhroz;Kim, Namgyu;Heo, Jun-Haeng
    • Smart Structures and Systems
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    • v.30 no.5
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    • pp.501-511
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    • 2022
  • Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

Parallel clustering technology for real-time LWIR band image processing (실시간 LWIR 밴드 영상 처리를 위한 병렬 클러스터링 기술)

  • Cho, Yongjin;Lee, Kyou-seung;Hong, Seongha;Oh, Jong-woo;Lee, DongHoon
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.158-158
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    • 2017
  • 비닐포장 하부에 위치한 콩의 생장 초기에 발생한 초엽을 인식하기 위한 연구를 수행중이다. 선행 연구에서 비닐포장에 접촉한 콩 초엽으로 인해 비닐포장 상부 표면의 열 반응 분포에 변화가 있음을 발견하였다. 현장에서 주행 중에 콩 초엽의 위치를 실시간으로 인식하고 연동된 선형 또는 회전형 엑츄에이터를 제어하여 정확한 위치에 천공을 수행하기 위해서는 계측 시스템과 제어 시스템간의 시간적 차이를 최소할 수 있는 실시간 신호 처리 기술이 필수적이다. 선행 연구에서 사용한 다중 IR 센서의 분해능은 $16{\times}4pixel$이며 주파수는 3 Hz로, 폭이 30cm 내외인 비닐포장 상부의 정밀 분석에 한계가 있음을 발견하였다. 이를 해결하기 위하여 분해능과 계측 주기를 개선할 수 있는 초소형 ($1cm{\times}1cm{\times}1cm$) 열화상 센서를 이용하였다. LWIR(Longwave infrared)영역에 해당하는 $8{\mu}m{\sim}14{\mu}m$의 영역에서 $0.05^{\circ}C$의 분해능을 보이는 $ Lepton^{TM}$ (500-0690-00, FLIR, Goleta, CA)모델을 사용하였다. 프레임당 $80{\times}60$ 픽셀의 정보가 2 Byte의 단위로 계측이 되며 9 Hz의 주파수로 대상면의 열 분포를 측정할 수 있다. 이론적으로 초당 정보 전송량은 86,400 Byte ($80{\times}60{\times}2{\times}9$)이며, 1 m를 진행하는 주행형 천공기에 적용할 경우 1 프레임당 10cm 정도의 면적을 측정하므로, 최대 위치 판정 분해능은 약 10 cm / 60 pixel = 0.17 cm/pixel로 상대적으로 정밀한 위치 판별이 가능하다. $80{\times}60{\times}2Byet$의 정보를 0.1초 이내에 분석해야 하는 기술적 과제를 해결하기 위하여 천공 작업기에 적합한 상용 SBC(Single board computer)의 클럭 속도(1 Ghz)로 처리 가능한 공간 분포 분석 알고리즘을 개발하였다. 전체 이미지 도메인을 한 번에 분석하는데 소요되는 시간을 최소화하기 위하여 공간정보 행렬을 균등히 배분하고 별도의 프로세서에서 Feature를 분석한 후 개별 프로세서의 결과를 경합식으로 판정하는 기술을 연구하였다. 오픈 소스인 MPICH(www.mpich.org) 라이브러리를 이용하여 개발한 신호 분석 프로그램을 클러스터링으로 연동된 개별 코어에 설치/수행 하였다. 2D 행렬인 열분포 정보를 공간적으로 균등 분배하여 개별 코어에서 행렬의 Spatial domain analysis를 수행하였다. $20{\times}20$의 클러스터링 단위를 이용할 경우 총 12개의 코어가 필요하였으며, 초당 10회의 연산이 가능함을 확인하였다. 병렬 클러스터링 기술을 이용하여 1m/s 내외의 주행 속도에 대응이 가능한 비닐포장 상부 열 분포 분석 시스템을 구현하였다.

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Performance Test for the Long Distance Sprayer by an Image Processing (영상처리를 이용한 광역방제기 팬의 성능실험)

  • Min, B.R.;Kim, D.W.;Seo, K.W.;Hong, J.T.;Kim, W.;Choi, J.H.;Lee, D.W.
    • Journal of Animal Environmental Science
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    • v.14 no.3
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    • pp.159-166
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    • 2008
  • This research was carried out to test and analyze capacity of the long distance sprayer fan in large livestock farmhouses. Long distance sprayer was manufactured to be able to spray a lot of water, which was a solvent for agricultural chemicals and black dye with the maximum spraying distance of 140 m and the effective spraying distance of 100 m. The spraying quantity and the distance were measured the intensity values of images within A4 papers, which absorbed the agricultural chemicals by spraying by binary image processing. These A4 papers were fixed upon the height of 1 m from soil ground at regular 10 m interval. After the A4 papers were collected and analyzed the intensity values of gray level. Gray level was ranged from 0 to 255, where 0 was black and 255 was white. A4 paper was fallen down from the stick at 10 m distance, because there were too large amount of sprayed water with black dye. Also, the paper showed low gray level at distance 30 m because of dropping lots of black water. The intensity value of gray level was showed almost less than 200 on the A4 papers between the distance 20 m and 100 m, which meant equality of spraying quantity. Additionally, it was possible to spay agricultural chemicals of until 180 m. Throughout this research, long distance sprayer could apply for preventing hoof-and-mouth disease in large livestock farmhouses.

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The Study of Optimal Acquisition Condition and Image Processing (최적의 촬영조건 및 영상처리에 관한 연구)

  • Lee, Yong-Gu;Shin, Jong-Ho;Seo, Kyoung-Eun;Choi, Yoo-Lee;Lee, Soo-Hyeon;Lee, Young-Jin;Kim, Hee-Joung
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.221-226
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    • 2014
  • In this paper, we achieved the study which determined the excellent diagnostic condition and searched the exposure condition with the minimum radiation exposure level having the equal diagnostic ability. To accomplish these study, chest phantom images with lesions and without ones were evaluated at various exposure conditions. With respect to the phantom with lesions and without ones, we obtained the chest PA imaging applied by photographing parts of DR apparatus and the images processed as histogram equalization and edge enhancement method. The images were acquired at the exposure conditions of 2.0, 2.5, 3.2, 4.0 and 5.0mAs. The morphological analysis was performed by ROC curves using the images obtained at each exposure condition. The exposure conditions with the most excellent diagnostic ability and with the equal diagnostic capability having the minimum radiation exposure level were determined by means of sensitivity, specificity and accuracy.

Information Hiding Technique in Smart Phone for the Implementation of GIS Web-Map Service (GIS 웹 맵 서비스 구현을 위한 스마트 폰에서의 정보은닉 기법)

  • Kim, Jin-Ho;Seo, Yong-Su;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.13 no.5
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    • pp.710-721
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    • 2010
  • Recently, for the advancement of embedded technology about mobile device, a new kind of service, mash-up is appeared. It is service or application combining multimedia content making tool or device and web-GIS(geographic information system) service in the mobile environment. This service can be ease to use for casual user and can apply in various ways. So, It is served in web 2.0 environment actively. But, in the mashup service, because generated multimedia contents linked with web map are new type of multimedia contents which include user's migration routes in the space such as GPS coordinates. Thus, there are no protection ways for intellectual property created by GIS web-map service users and user's privacy. In this paper, we proposed a location and user information hiding scheme for GIS web-map service. This scheme embeds location and user information into a picture that is taken by camera module on the mobile phone. It is not only protecting way for user's privacy but is also tracing way against illegal photographer who is peeping person through hidden camera. And than, we also realized proposed scheme on the mobile smart phone. For minimizing margin of error about location coordinate value against contents manipulating attacks, GPS information is embedded into chrominance signal of contents considering weight of each digit about binary type of GPS coordinate value. And for tracing illegal photographer, user information such as serial number of mobile phone, phone number and photographing date is embedded into frequency spectrum of contents luminance signal. In the experimental results, we confirmed that the error of extracted information against various image processing attacks is within reliable tolerance. And after file format translation attack, we extracted embedded information from the attacked contents without no damage. Using similarity between extracted one and original templete, we also extracted whole information from damaged chrominance signal of contents by various image processing attacks.