• Title/Summary/Keyword: feature points

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A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

  • Daoud, Mosaab
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.7.1-7.7
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    • 2020
  • In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

Height extraction of the man-made structure including occluded region using trinocular matching and DEM mapping (Trinocular 정합과 DEM 변환식을 이용한 차폐지역이 포함된 인공지물의 높이 추출)

  • 김지태;엄기문;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.260-263
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    • 1996
  • THe Purpose of this paper is to match the feature point of man-made structure and to obtain the DEM which are occluded in a image plane. We use the trinocular matching with epipolar lines and planes. If an occlusion appears at one of the trinocular images, the DEM mapping is used to estimate the height of feature points in it.

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Development of OMM Module for PC-NC System (PC-NC 를 위한 기상측정 모듈 개발)

  • 윤길상;권양훈;정석우;조명우
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.8
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    • pp.144-152
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    • 2003
  • The purpose of this paper is to establish an effective inspection system by using OMM (On-Machine Measurement) system based PC-NC. This system can reduce manufacturing lead time because part is inspected each process. Inspection process planning is accomplished by determining the number of measuring points, their location, measuring path using fuzzy logic, Hammersley method, traveling salesperson problem. Inspection with contacted sensor improve quality as inspection feature is developed to based machining feature. This method is tested by simulation and experiment, then analyzed measuring data and geometry tolerance.

Some Worthy Signal Processing Techniques for Mechanical Fault Diagnosis

  • Chan, Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.39-52
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    • 2002
  • Research Direction The significant research direction in mechanical fault diagnosis area: Theorles and approaches for fault feature extracting and fault classification. Identification Complicated fault generating mechanism and its model Intelligent fault diagnosis system (including the expert system and network based remote diagnosis system) One of the Key Points: Fault feature extracting techniques based on (modern) signal processing(omitted)

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Feature based Text Watermarking in Digital Binary Image (이진 문서 영상에서의 특징 기반 텍스트 워터마킹)

  • 공영민;추현곤;최종욱;김희율
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.359-362
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    • 2002
  • In this paper, we propose a new feature-based text watermarking for the binary text image. The structure of specific characters from preprocessed text image are modified to embed watermark. Watermark message are embedded and detected by the following method; Hole line disconnect using the connectivity of the character containing a hole, Center line shift using the hole area and Differential encoding using difference of flippable score points. Experimental results show that the proposed method is robust to rotation and scaling distortion.

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The Detection of the Stereo Viewing Points for 3D Object Recognition (2차원 물체 인식을 위한 입체 시각 포인트의 추출)

  • Seo, Choon-Weon;Won, Young-Jin
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.451-452
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    • 2007
  • It is need to find a new feature for the more statable recognition system. Now, we need more features like a human eyes. Therefore, this paper proposed a new feature with the stereo camera. In this paper, the each different features from the left and right input image will be extracted by stereo vision system, and will be good for the 3-D recognition.

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Robust Reference Point and Feature Extraction Method for Fingerprint Verification using Gradient Probabilistic Model (지문 인식을 위한 Gradient의 확률 모델을 이용하는 강인한 기준점 검출 및 특징 추출 방법)

  • 박준범;고한석
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.6
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    • pp.95-105
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    • 2003
  • A novel reference point detection method is proposed by exploiting tile gradient probabilistic model that captures the curvature information of fingerprint. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in a probabilistic sense. The uniformly distributed gradient texture represents either the core point itself or those of similar points that can be used to establish the rigid reference from which to map the features for recognition. Key benefits are reductions in preprocessing and consistency of locating the same points as the reference points even when processing arch type fingerprints. Moreover, the new feature extraction method is proposed by improving the existing feature extraction using filterbank method. Experimental results indicate the superiority of tile proposed scheme in terms of computational time in feature extraction and verification rate in various noisy environments. In particular, the proposed gradient probabilistic model achieved 49% improvement under ambient noise, 39.2% under brightness noise and 15.7% under a salt and pepper noise environment, respectively, in FAR for the arch type fingerprints. Moreover, a reduction of 0.07sec in reference point detection time of the GPM is shown possible compared to using the leading the poincare index method and a reduction of 0.06sec in code extraction time of the new filterbank mettled is shown possible compared to using the leading the existing filterbank method.

Moving Object Detection and Tracking Techniques for Error Reduction (오인식률 감소를 위한 이동 물체 검출 및 추적 기법)

  • Hwang, Seung-Jun;Ko, Ha-Yoon;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.22 no.1
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    • pp.20-26
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    • 2018
  • In this paper, we propose a moving object detection and tracking algorithm based on multi-frame feature point tracking information to reduce false positives. However, there are problems of detection error and tracking speed in existing studies. In order to compensate for this, we first calculate the corner feature points and the optical flow of multiple frames for camera movement compensation and object tracking. Next, the tracking error of the optical flow is reduced by the multi-frame forward-backward tracking, and the traced feature points are divided into the background and the moving object candidate based on homography and RANSAC algorithm for camera movement compensation. Among the transformed corner feature points, the outlier points removed by the RANSAC are clustered and the outlier cluster of a certain size is classified as the moving object candidate. Objects classified as moving object candidates are tracked according to label tracking based data association analysis. In this paper, we prove that the proposed algorithm improves both precision and recall compared with existing algorithms by using quadrotor image - based detection and tracking performance experiments.

Development of robot calibration method based on 3D laser scanning system for Off-Line Programming (오프라인 프로그래밍을 위한 3차원 레이저 스캐닝 시스템 기반의 로봇 캘리브레이션 방법 개발)

  • Kim, Hyun-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.3
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    • pp.16-22
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    • 2019
  • Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

A Method for Effective Homography Estimation Applying a Depth Image-Based Filter (깊이 영상 기반 필터를 적용한 효과적인 호모그래피 추정 방법)

  • Joo, Yong-Joon;Hong, Myung-Duk;Yoon, Ui-Nyoung;Go, Seung-Hyun;Jo, Geun-Sik
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.2
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    • pp.61-66
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    • 2019
  • Augmented reality is a technology that makes a virtual object appear as if it exists in reality by composing a virtual object in real time with the image captured by the camera. In order to augment the virtual object on the object existing in reality, the homography of images utilized to estimate the position and orientation of the object. The homography can be estimated by applying the RANSAC algorithm to the feature points of the images. But the homography estimation method using the RANSAC algorithm has a problem that accurate homography can not be estimated when there are many feature points in the background. In this paper, we propose a method to filter feature points of a background when the object is near and the background is relatively far away. First, we classified the depth image into relatively near region and a distant region using the Otsu's method and improve homography estimation performance by filtering feature points on the relatively distant area. As a result of experiment, processing time is shortened 71.7% compared to a conventional homography estimation method, and the number of iterations of the RANSAC algorithm was reduced 69.4%, and Inlier rate was increased 16.9%.