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  • Title/Summary/Keyword: 유클리드 거리

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Displacement Measurement of Structure using Multi-View Camera & Photogrammetry (사진측량법과 다시점 카메라를 이용한 구조물의 변위계측)

  • Yeo, Jeong-Hyeon;Yoon, In-Mo;Jeong, Young-Kee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.1141-1144
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    • 2005
  • In this paper, we propose an automatic displacement system for testing stability of structure. Photogrammetry is a method which can measure accurate 3D data from 2D images taken from different locations and which is suitable for analyzing and measuring the displacement of structure. This paper consists of camera calibration, feature extraction using coded target & retro-reflective circle, 3D reconstruction and analyzing accuracy. Multi-view camera which is used for measuring displacement of structure is placed with different location respectively. Camera calibration calculates trifocal tensor from corresponding points in images, from which Euclidean camera is calculated. Especially, in a step of feature extraction, we utilize sub-pixel method and pattern recognition in order to measure the accurate 3D locations. Scale bar is used as reference to measure. the accurate value of world coordinate..

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Objective Quality Assessment Method for Stitched Images (스티칭 영상의 객관적 영상화질의 평가 방법)

  • Billah, Meer Sadeq;Ahn, Heejune
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.227-234
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    • 2018
  • Recently, stitching techniques are used for obtaining wide FOV, e.g., panorama contents, from normal cameras. Despite many proposed algorithms, the no objective quality evaluation method is developed, so the comparison of algorithms are performed only in subjective way. The paper proposes a 'Delaunay-triangulation based objective assessment method' for evaluating the geometric and photometric distortions of stitched or warped images. The reference and target images are segmented by Delaunay-triangulation based on matched points between two images, the average Euclidian distance is used for geometric distortion measure, and the average or histogram of PSNR for photometric measure. We shows preliminary results with several test images and stitching methods for demonstrate the benefits and application.

Enhanced Polynomial Selection Method for GNFS (GNFS를 위한 향상된 다항식 선택 기법)

  • Kim, Suhri;Kwon, Jihoon;Cho, Sungmin;Chang, Nam Su;Yoon, Kisoon;Han, Chang;Park, Young-Ho;Hong, Seokhie
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.5
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    • pp.1121-1130
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    • 2016
  • RSA cryptosystem is one of the most widely used public key cryptosystem. The security of RSA cryptosystem is based on hardness of factoring large number and hence there are ongoing attempt to factor RSA modulus. General Number Field Sieve (GNFS) is currently the fastest known method for factoring large numbers so that CADO-NFS - publicly well-known software that was used to factor RSA-704 - is also based on GNFS. However, one disadvantage is that CADO-NFS could not always select the optimal polynomial for given parameters. In this paper, we analyze CADO-NFS's polynomial selection stage. We propose modified polynomial selection using Chinese Remainder Theorem and Euclidean Distance. In this way, we can always select polynomial better than original version of CADO-NFS and expected to use for factoring RSA-1024.

3D Face Recognition using Projection Vectors for the Area in Contour Lines (등고선 영역의 투영 벡터를 이용한 3차원 얼굴 인식)

  • 이영학;심재창;이태홍
    • Journal of Korea Multimedia Society
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    • v.6 no.2
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    • pp.230-239
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    • 2003
  • This paper presents face recognition algorithm using projection vector reflecting local feature for the area in contour lines. The outline shape of a face has many difficulties to distinguish people because human has similar face shape. For 3 dimensional(3D) face images include depth information, we can extract different face shapes from the nose tip using some depth values for a face image. In this thesis deals with 3D face image, because the extraction of contour lines from 2 dimensional face images is hard work. After finding nose tip, we extract two areas in the contour lilies from some depth values from 3D face image which is obtained by 3D laser scanner. And we propose a method of projection vector to localize the characteristics of image and reduce the number of index data in database. Euclidean distance is used to compare of similarity between two images. Proposed algorithm can be made recognition rate of 94.3% for face shapes using depth information.

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Improved Density-Independent Fuzzy Clustering Using Regularization (레귤러라이제이션 기반 개선된 밀도 무관 퍼지 클러스터링)

  • Han, Soowhan;Heo, Gyeongyong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.1
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    • pp.1-7
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    • 2020
  • Fuzzy clustering, represented by FCM(Fuzzy C-Means), is a simple and efficient clustering method. However, the object function in FCM makes clusters affect clustering results proportional to the density of clusters, which can distort clustering results due to density difference between clusters. One method to alleviate this density problem is EDI-FCM(Extended Density-Independent FCM), which adds additional terms to the objective function of FCM to compensate for the density difference. In this paper, proposed is an enhanced EDI-FCM using regularization, Regularized EDI-FCM. Regularization is commonly used to make a solution space smooth and an algorithm noise insensitive. In clustering, regularization can reduce the effect of a high-density cluster on clustering results. The proposed method converges quickly and accurately to real centers when compared with FCM and EDI-FCM, which can be verified with experimental results.

Machine Learning-Based Malicious URL Detection Technique (머신러닝 기반 악성 URL 탐지 기법)

  • Han, Chae-rim;Yun, Su-hyun;Han, Myeong-jin;Lee, Il-Gu
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.3
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    • pp.555-564
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    • 2022
  • Recently, cyberattacks are using hacking techniques utilizing intelligent and advanced malicious codes for non-face-to-face environments such as telecommuting, telemedicine, and automatic industrial facilities, and the damage is increasing. Traditional information protection systems, such as anti-virus, are a method of detecting known malicious URLs based on signature patterns, so unknown malicious URLs cannot be detected. In addition, the conventional static analysis-based malicious URL detection method is vulnerable to dynamic loading and cryptographic attacks. This study proposes a technique for efficiently detecting malicious URLs by dynamically learning malicious URL data. In the proposed detection technique, malicious codes are classified using machine learning-based feature selection algorithms, and the accuracy is improved by removing obfuscation elements after preprocessing using Weighted Euclidean Distance(WED). According to the experimental results, the proposed machine learning-based malicious URL detection technique shows an accuracy of 89.17%, which is improved by 2.82% compared to the conventional method.

Estimation of Urban Flood Risk Forecasting Standard using Local Disaster Prevention Performance (지역 방재성능을 고려한 도시홍수 위험 예보기준 산정에 관한 연구)

  • Lee, Seon Mi;Choi, Youngje;Yi, Jaeeung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.154-154
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    • 2020
  • 최근 국지성 호우가 빈번하게 발생하고 있고, 이로 인해 국내 도시지역 홍수피해 발생빈도와 피해규모가 증가하고 있다. 2010년, 2011년, 2018년에 서울에서는 홍수로 인한 침수피해가 크게 발생하여 많은 인명과 재산의 피해가 있었다. 이렇듯 도시지역은 타 지역에 비해 인구와 재산이 밀집되어 있어 홍수 취약성이 상대적으로 높은 지역이다. 국내에서는 홍수피해 저감을 위해 홍수예보를 발령하고 있다. 하지만 국내 홍수예보는 국가하천 및 지방하천의 주요 하천 구간에서만 실시되고 있어 이러한 하천에 접하지 않는 지역은 국가 홍수예보의 수혜를 받을 수 없다. 그렇기 때문에 각 지역에서는 홍수 대응을 위해 기상청의 호우특보 기준을 사용하고 있으며 이 기준은 전국적으로 동일하다는 특징이 있다. 하지만 각 도시지역은 과거 홍수피해에 따라 방재시설을 추가로 설치하거나 보수하고 있어 각 지역의 방재시설 현황 및 홍수에 대한 취약성 정도가 다른 상황이다. 그러므로 전국적으로 동일한 강우기준이 적용되어 발령되고 있는 호우 특보는 실제 각 도시지역의 방재현황이 고려되지 못한다는 문제가 있다. 이와 관련하여 과거 낙동강 지역을 대상으로 지역별 홍수위험도에 따른 홍수위험지수를 산정하고 검토한 연구가 수행된 바 있다. 본 연구에서는 각 도시지역의 방재 현황을 고려하여 강우기준을 보정할 수 있는 가중치를 산정하는 방안에 대해 제시하였다. 이를 위해 서울 지역 25개 기초지자체를 대상으로 연구를 진행하였으며, 홍수 취약성을 평가하기 위한 세부인자는 노출도, 민감도, 적응도로 구분하였다. 각 세부인자 별 가중치를 산정하기 위해서는 엔트로피 방법을 적용하였고, 산정된 결과를 이용하여 각 지역 별 가중치를 산정하기 위해서는 유클리드 거리 산정법을 적용하였다. 그 결과 각 지역의 방재 특성을 고려한 가중치를 산정할 수 있었으며 향후에는 지역 별 방재특성이 고려된 강우기준을 제시 및 적용성을 검토할 계획이다.

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Computer Vision-Based Measurement Method for Wire Harness Defect Classification

  • Yun Jung Hong;Geon Lee;Jiyoung Woo
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.77-84
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    • 2024
  • In this paper, we propose a method for accurately and rapidly detecting defects in wire harnesses by utilizing computer vision to calculate six crucial measurement values: the length of crimped terminals, the dimensions (width) of terminal ends, and the width of crimped sections (wire and core portions). We employ Harris corner detection to locate object positions from two types of data. Additionally, we generate reference points for extracting measurement values by utilizing features specific to each measurement area and exploiting the contrast in shading between the background and objects, thus reflecting the slope of each sample. Subsequently, we introduce a method using the Euclidean distance and correction coefficients to predict values, allowing for the prediction of measurements regardless of changes in the wire's position. We achieve high accuracy for each measurement type, 99.1%, 98.7%, 92.6%, 92.5%, 99.9%, and 99.7%, achieving outstanding overall average accuracy of 97% across all measurements. This inspection method not only addresses the limitations of conventional visual inspections but also yields excellent results with a small amount of data. Moreover, relying solely on image processing, it is expected to be more cost-effective and applicable with less data compared to deep learning methods.

A study on the active sonar reverberation suppression method based on non-negative matrix factorization with beta-divergence function (베타-발산 함수를 활용한 비음수 행렬 분해 기반의 능동 소나 잔향 제거 기법에 대한 연구)

  • Seokjin Lee;Geunhwan Kim
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.4
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    • pp.369-382
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    • 2024
  • To suppress the reverberation in the active sonar system, the non-negative matrix factorization-based reverberation suppression methods have been researched recently. An estimation loss function, which makes the multiplication of basis matrices same as the input signals, has to be considered to design the non-negative matrix factorization methods, but the conventional method simply chooses the Kullback-Leibler divergence asthe lossfunction without any considerations. In this paper, we examined that the Kullback-Leibler divergence is the best lossfunction or there isthe other loss function enhancing the performance. First, we derived a modified reverberation suppression algorithm using the generalized beta-divergence function, which includes the Kullback-Leibler divergence. Then, we performed Monte-Carlo simulations using synthesized reverberation for the modified reverberation suppression method. The results showed that the Kullback-Leibler divergence function (β = 1) has good performances in the high signal-to-reverberation environments, but the intermediate function (β = 1.25) between Kullback-Leibler divergence and Euclidean distance has better performance in the low signal-to-reverberation environments.

A Study on an Open/Closed Eye Detection Algorithm for Drowsy Driver Detection (운전자 졸음 검출을 위한 눈 개폐 검출 알고리즘 연구)

  • Kim, TaeHyeong;Lim, Woong;Sim, Donggyu
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.7
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    • pp.67-77
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    • 2016
  • In this paper, we propose an algorithm for open/closed eye detection based on modified Hausdorff distance. The proposed algorithm consists of two parts, face detection and open/closed eye detection parts. To detect faces in an image, MCT (Modified Census Transform) is employed based on characteristics of the local structure which uses relative pixel values in the area with fixed size. Then, the coordinates of eyes are found and open/closed eyes are detected using MHD (Modified Hausdorff Distance) in the detected face region. Firstly, face detection process creates an MCT image in terms of various face images and extract criteria features by PCA(Principle Component Analysis) on offline. After extraction of criteria features, it detects a face region via the process which compares features newly extracted from the input face image and criteria features by using Euclidean distance. Afterward, the process finds out the coordinates of eyes and detects open/closed eye using template matching based on MHD in each eye region. In performance evaluation, the proposed algorithm achieved 94.04% accuracy in average for open/closed eye detection in terms of test video sequences of gray scale with 30FPS/320×180 resolution.