• Title/Summary/Keyword: Image Edge

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A Study on Finding the Rail Space in Elevators Using Matched Filter

  • Song, Myong-Lyol
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.57-65
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    • 2019
  • In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

Event Horizon Telescope : Earth-sized mm-VLBI array to image supermassive black holes

  • Kim, Jae-Young
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.59.1-59.1
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    • 2019
  • Immediate vicinity of a supermassive black hole (SMBH) is an important place to test general relativity in strong gravity regime. Also, this is a place where mass accretion and jet formation actively occurs at the centers of active galaxies. Theoretical studies predict presence of bright ring-like emission encircling an accreting SMBH with a diameter of about 5 Schwarzschild radii, and a flux depression at the center (i.e., BH shadow). Direct imaging of the BH shadow is accordingly of great importance in modern astrophysics. However, the angular sizes of the horizon-scale structures are desperately small (e.g., ~40-50 microarcseconds (uas) diameter for the nearest best candidates). This poses serious challenges to observe them directly. Event Horizon Telescope (EHT) is a global network of sensitive radio telescopes operating at 230 GHz (1.3 mm), providing ultra-high angular resolution of 20 uas by cutting-edge very long baseline interferometry techniques. With this resolution, EHT aims to directly image the nearest SMBHs; M87 and the galactic center Sgr $A{\ast}$ (~40-50 uas diameters). In Spring 2017, the EHT collaboration conducted a global campaign of EHT and multiwavelength observations of M87 and Sgr $A{\ast}$, with addition of the phased ALMA to the 1.3mm VLBI array. In this talk, I review results from past mm-VLBI and EHT observations, provide updates on the results from the 2017 campaign, and future perspectives.

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Design of Portable Intelligent Surveillance System based on Edge Cloud and Micro Cloud (에지 클라우드 및 마이크로 클라우드 기반의 이동형 지능 영상감시 시스템 설계)

  • Park, Sun;Cha, ByungRae;Kim, JongWon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.556-557
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    • 2019
  • The current video surveillance system is the third generation, and the video device has developed from low image quality to high image quality. The video surveillance solution has improved from the simple type to the intelligent type. However, as the equipment and technology for these video surveillance systems become more complicated and diversified, they are increasingly dependent on infrastructure, such as faster network speed and stable power supply. On the other hand, there is a growing need for video surveillance in areas where basic infrastructure is limited, such as power and communications. In this paper, we propose a system that can support intelligent video surveillance in a region where basic infrastructure is limited.

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Robust Image Watermarking via Perceptual Structural Regularity-based JND Model

  • Wang, Chunxing;Xu, Meiling;Wan, Wenbo;Wang, Jian;Meng, Lili;Li, Jing;Sun, Jiande
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.1080-1099
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    • 2019
  • A better tradeoff between robustness and invisibility will be realized by using the just noticeable (JND) model into the quantization-based watermarking scheme. The JND model is usually used to describe the perception characteristics of human visual systems (HVS). According to the research of cognitive science, HVS can adaptively extract the structure features of an image. However, the existing JND models in the watermarking scheme do not consider the structure features. Therefore, a novel JND model is proposed, which includes three aspects: contrast sensitivity function, luminance adaptation, and contrast masking (CM). In this model, the CM effect is modeled by analyzing the direction features and texture complexity, which meets the human visual perception characteristics and matches well with the spread transform dither modulation (STDM) watermarking framework by employing a new method to measure edge intensity. Compared with the other existing JND models, the proposed JND model based on structural regularity is more efficient and applicable in the STDM watermarking scheme. In terms of the experimental results, the proposed scheme performs better than the other watermarking scheme based on the existing JND models.

Method of Video Stitching based on Minimal Error Seam (최소 오류 경계를 활용한 동적 물체 기반 동영상 정합 방안)

  • Kang, Jeonho;Kim, Junsik;Kim, Sang-IL;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.24 no.1
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    • pp.142-152
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    • 2019
  • There is growing interest in ultra-high-resolution content that gives a more realistic sense of presence than existing broadcast content. However, in order to provide ultra-high-resolution contents in existing broadcast services, there are limitations in view angle and resolution of the image acquisition device. In order to solve this problem, many researches on stitching, which is an image synthesis method using a plurality of input devices, have been conducted. In this paper, we propose method of dynamic object based video stitching using minimal error seam in order to overcome the temporal invariance degradation of moving objects in the stitching process of horizontally oriented videos.

Detecting Numeric and Character Areas of Low-quality License Plate Images using YOLOv4 Algorithm (YOLOv4 알고리즘을 이용한 저품질 자동차 번호판 영상의 숫자 및 문자영역 검출)

  • Lee, Jeonghwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.4
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    • pp.1-11
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    • 2022
  • Recently, research on license plate recognition, which is a core technology of an intelligent transportation system(ITS), is being actively conducted. In this paper, we propose a method to extract numbers and characters from low-quality license plate images by applying the YOLOv4 algorithm. YOLOv4 is a one-stage object detection method using convolution neural network including BACKBONE, NECK, and HEAD parts. It is a method of detecting objects in real time rather than the previous two-stage object detection method such as the faster R-CNN. In this paper, we studied a method to directly extract number and character regions from low-quality license plate images without additional edge detection and image segmentation processes. In order to evaluate the performance of the proposed method we experimented with 500 license plate images. In this experiment, 350 images were used for training and the remaining 150 images were used for the testing process. Computer simulations show that the mean average precision of detecting number and character regions on vehicle license plates was about 93.8%.

Smart Mirror for Facial Expression Recognition Based on Convolution Neural Network (컨볼루션 신경망 기반 표정인식 스마트 미러)

  • Choi, Sung Hwan;Yu, Yun Seop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.200-203
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    • 2021
  • This paper introduces a smart mirror technology that recognizes a person's facial expressions through image classification among several artificial intelligence technologies and presents them in a mirror. 5 types of facial expression images are trained through artificial intelligence. When someone looks at the smart mirror, the mirror recognizes my expression and shows the recognized result in the mirror. The dataset fer2013 provided by kaggle used the faces of several people to be separated by facial expressions. For image classification, the network structure is trained using convolution neural network (CNN). The face is recognized and presented on the screen in the smart mirror with the embedded board such as Raspberry Pi4.

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The Construction Method of Precise DTM of UAV Images Using Sobel-median Filtering (소벨-메디언 필터링을 이용한 UAV 영상의 정밀 DTM 구축 방법에 관한 연구)

  • Na, Young-Woo
    • Journal of Urban Science
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    • v.12 no.2
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    • pp.43-52
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    • 2023
  • UAV have the disadvantage that are weak from rainfall or winds due to the light platform, so use Scale-Invariant Feature Transform (SIFT) method which extrude keypoints in image matching process. To find the efficient filtering method for the construction of precise Digital Terrain Model (DTM) using UAV images, comparatively analyzed sobel and Differential of Gaussian (DoG) and found sobel is more efficient way to extrude buildings, trees, and so on. And edges are extruded more clearly when applying median additionally which have the merit of preserving edge and eliminating noise. In this study, applied sobel-median filtering which plus median to sobel and constructed the 1st filtered DTM that extrude building and trees and 2nd filtered DTM that extrude cars by threshold of gradient, Analysis of the degree of accuracy improvement showed that standard deviations of 1st filtered DTM and 2nd filtered DTM are 0.32m, 0.287m respectively, and both are acceptable for the tolerance of 0.33m for elevation points of 1/1,000 digital map, and the accuracy was increased about 10% by filtering automobiles. Plus, moving things are changed those position and direction in every image, and these are not target to filter because of the characteristic that is excluded from SIFT method.

Experimental study of turbulent flow in a scaled RPV model by PIV technology

  • Luguo Liu;Wenhai Qu;Yu Liu;Jinbiao Xiong;Songwei Li;Guangming Jiang
    • Nuclear Engineering and Technology
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    • v.56 no.7
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    • pp.2458-2473
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    • 2024
  • The turbulent flow in reactor pressure vessel (RPV) of pressurized water reactor (PWR) is important for the flow rate distribution at core inlet. Thus, it is vital to study the turbulent flow phenomena in RPV. However, the complicated fluid channel consisted of inner structures of RPV will block or refract the laser sheet of particle image velocimetry (PIV). In this work, the matched index of refraction (MIR) of sodium iodide (NaI) solution and acrylic was applied to support optical path for flow field measurements by PIV in the 1/10th scaled-down RPV model. The experimental results show detailed velocity field at different locations inside the scaled-down RPV model. Some interesting phenomena are obtained, including the non-negligible counterflow at the corner of nozzle edge, the high downward flowing stream in downcomer, large vortices above vortex suppression plate in lower plenum. And the intensity of counterflow and the strength of vortices increase as inlet flow rate increasing. Finally, the case of asymmetry flow was also studied. The turbulent flow has different pattern compared with the case of symmetrical inlet flow rate, which may affect the uniformity of flow distribution at the core inlet.

A Study on the Extraction of a River from the RapidEye Image Using ISODATA Algorithm (ISODATA 기법을 이용한 RapidEye 영상으로부터 하천의 추출에 관한 연구)

  • Jo, Myung-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.4
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    • pp.1-14
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    • 2012
  • A river is defined as the watercourse flowing through its channel, and the mapping tasks of a river plays an important role for the research on the topographic changes in the riparian zones and the research on the monitoring of flooding in its floodplain. However, the utilization of the ground surveying technologies is not efficient for the mapping tasks of a river due to the irregular surfaces of the riparian zones and the dynamic changes of water level of a river. Recently, the spatial information data sets are widely used for the coastal mapping tasks due to the acquisition of the topographic information without human accessibility. In this research, we tried to extract a river from the RapidEye imagery by using the ISODATA(Iterative Self_Organizing Data Analysis) classification algorithm with the two different parameters(NIR (Near Infra-Red) band and NDVI(Normalized Difference Vegetation Index)). First, the two different images(the NIR band image and the NDVI image) were generated from the RapidEye imagery. Second, the ISODATA algorithm were applied to each image and each river was generated in each image through the post-processing steps. River boundaries were also extracted from each classified image using the Sobel edge detection algorithm. Ground truths determined by the experienced expert are used for the assessment of the accuracy of an each generated river. Statistical results show that the extracted river using the NIR band has higher accuracies than the extracted river using the NDVI.