• Title/Summary/Keyword: 정합추적

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Gabor Pulse-Based Matching Pursuit Algorithm : Applications in Waveguide Damage Detection (가보 펄스 기반 정합추적 알고리즘 : 웨이브가이드 결함진단에서의 응용)

  • 선경호;홍진철;김윤영
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.969-974
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    • 2004
  • Although guided-waves are very efficient for long-range nondestructive damage inspection, it is not easy to extract meaningful pulses of small magnitude out of noisy signals. The ultimate goal of this research is to develop an efficient signal processing technique for the current guided-wave technology. The specific contribution of this investigation towards achieving this goal, a two-stage Gabor pulse-based matching pursuit algorithm is proposed : rough approximations with a set for predetermined parameters characterizing the Gabor pulse and fine adjustments of the parameters by optimization. The parameters estimated from the measured signal are then used to assess not only the location but also the size of a crack existing in a rod. To validate the effectiveness of the proposed method, the longitudinal wave-based damage detection in rods is considered. To estimate the crack size, Love's theory for the dispersion of longitudinal waves is employed.

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Matching Pursuit Approach for Guided Wave-Based Damage Inspection (유도 초음파 이용 결함 진단을 위한 정합추적 기법)

  • Hong, Jin-Chul;Sun, Kyung-Ho;Kim, Yoon-Young
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.11a
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    • pp.615-618
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    • 2004
  • For successful guided-wave damage inspection, the appropriate signal processing of measured wave signals is very important. The objective of this paper is to introduce an efficient signal processing technique especially suitable for the guided-waves used for damage detection. The key idea of this technique is to model guided-waves by chirp functions of special form considering the dispersion phenomenon. To determine the parameter of the chirp functions simulating guided-waves, the matching pursuit algorithm is employed. The damage information in waveguides can be extracted by pulse-characterizing parameters. The effectiveness of present method is checked with the longitudinal wave-based damage inspection.

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Algorithm for Moving Object Tracking from Moving Camera Using Histogram Projection (히스토그램 프로젝션을 이용한 움직이는 카메라로 부터의 이동물체 추적 알고리즘)

  • 설성욱;이희봉;김효성;남기곤;이철헌
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.4
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    • pp.38-45
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    • 2001
  • In this paper, we propose an algorithm for moving object tracking from moving camera using histogram back program intersection(HI) and XY-projection The proposed method segments objects using histogram back projection, matches tracing objects using histogram intersection and extracts them using XY- projection. Through the simulation this paper shows that the proposed method segments. matches and tracks objects without significant error image sequences obtained by moving camera.

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Pulmonary Nodule Registration using Template Matching in Serial CT Scans (연속 CT 영상에서 템플릿 매칭을 이용한 폐결절 정합)

  • Jo, Hyun-Hee;Hong, He-Len
    • Journal of KIISE:Software and Applications
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    • v.36 no.8
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    • pp.623-632
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    • 2009
  • In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

Stereo Object Tracking using BMA and JTC (BMA와 JTC를 이용한 스테레오 물체추적)

  • 고정환;이재수;이용선;김은수
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.641-644
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    • 1999
  • 스테레오 물체 추적기는 좌. 우측 카메라의 스테레오 입력 영상에서 이동 물체의 주시각을 제어하면서 자동으로 추적 물체가 항상 영상의 중앙에 위치하도록 제어해야 한다. 본 논문에서는 복잡한 배경이 존재하고 카메라가 움직이는 경우 스테레오 물체 추적을 위한 방법으로 블록 정합 알고리즘(BMA)으로 추적 물체와 배경을 분리하고, JTC를 이용해 주시각 및 팬/틸트 제어 값을 구하여 좌, 우측 카메라를 제어하는 스테레오 자동 물체 추적 시스템을 제시하였다. 추적결과 배경잡음에 상관없이 적응적으로 작용하여 정확히 이동 물체의 위치를 스테레오로 추적할 수 있었다.

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Real-time Moving Object Tracking from a Moving Camera (이동 카메라 영상에서 이동물체의 실시간 추적)

  • Chun, Quan;Lee, Ju-Shin
    • The KIPS Transactions:PartB
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    • v.9B no.4
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    • pp.465-470
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    • 2002
  • This paper presents a new model based method for tracking moving object from a moving camera. In the proposed method, binary model is derived from detected object regions and Hausdorff distance between the model and edge image is used as its similarity measure to overcome the target's shape changes. Also, a novel search algorithm and some optimization methods are proposed to enable realtime processing. The experimental results on our test sequences demonstrate the high efficiency and accuracy of our approach.

Stereo object Tracking System using Block Matching Algorithm and optical JTC (블록정합 알고리즘과 광 JTC를 이용한 스테레오 물체추적 시스템)

  • 이재수;이용범;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.3B
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    • pp.549-556
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    • 2000
  • In this paper, we propose a new adaptive stereo object tracking system that can be used when the back ground image is complex and the cameras are not fixed . In this method, we used the Block Matching Algorithm to separate the tracking object form the background image and then the optical JTC system is used to obtain the convergence-controlling and pa/tilt-controlling values fro the left and right cameras. the experimental results are found to track the object robustly & adaptively for the object tracking in various background images, and the possibility of real-time implementation of the proposed system by using the optical JTC is also suggested.

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A Study on Tracking of Object in Image Sequence (동영상내의 물체 추적에 관한 연구)

  • Choi Ho-Jin;Park Seung-Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.05a
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    • pp.665-668
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    • 2006
  • 이동 물체 검출 및 추적은 과중한 연산량에 의해 초당 처리할 수 있는 프레임의 수가 적게 되거나 정합 과정이 단순하여 추적을 실패하는 문제점들이 있다. 본 논문에서는 동영상내에서 이동 물체를 검출하고 추적하는 새로운 접근 방법을 제안한다. 입력된 영상으로부터 배경과 물체를 분리하기 위해 background subtraction을 이용하였고, 분리된 물체들은 이진 연결 요소 분석을 통하여 세그먼트 된다. 그리고 물체의 추적을 위하여 Kalman filter를 사용하였다. 본 논문의 실험에서는 야외에서 촬영한 비디오 시퀀스를 이용하였으며, 물체 검출 및 추적이 조명 변화, 그림자에도 잘 적응함을 증명하였다.

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A Vehicle Tracking Algorithm Focused on the Initialization of Vehicle Detection-and Distance Estimation (초기 차량 검출 및 거리 추정을 중심으로 한 차량 추적 알고리즘)

  • 이철헌;설성욱;김효성;남기곤;주재흠
    • Journal of KIISE:Software and Applications
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    • v.31 no.11
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    • pp.1496-1504
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    • 2004
  • In this paper, we propose an algorithm for initializing a target vehicle detection, tracking the vehicle and estimating the distance from it on the stereo images acquired from a forward-looking stereo camera mounted on a road driving vehicle. The process of vehicle detection extracts road region using lane recognition and searches vehicle feature from road region. The distance of tracking vehicle is estimated by TSS correlogram matching from stereo Images. Through the simulation, this paper shows that the proposed method segments, matches and tracks vehicles robustly from image sequences obtained by moving stereo camera.

Fast keypoint matching using clustering of binary descriptors (이진 특징 기술자의 군집화를 이용한 특징점 고속 정합)

  • Park, Jungsik;Park, Jong-Il
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.11a
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    • pp.9-10
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    • 2012
  • 이진 특징 기술자는 실수 벡터 형태의 특징 기술자보다 빠르게 특징점 추출 및 정합이 가능하고 메모리 공간도 적게 차지하는 장점이 있다. 하지만, 특징점의 수가 많아질수록 정합에 많은 시간이 소요되므로 실시간 처리가 중요한 객체 추적에 적용하기 위해서는 정합의 고속화 방법에 대한 연구가 필요하다. 이에 본 논문에서는 이진 특징 기술자의 군집화를 통한 특징점의 고속 정합 방법을 제안한다. 제안된 방법은 k-means 군집화 알고리즘을 기반으로 정합을 위한 기술자 탐색을 효과적으로 수행함으로써 군집화를 사용하지 않는 기존의 정합 방법에 비해 빠르면서도 높은 정확도를 유지한다.

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