• Title/Summary/Keyword: object matching

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A Study on Measurement Range Extension for Atomic Force Microscope (원자간력 현미경의 측정면적 확대에 관한 연구)

  • Ko Myung-Jun;Patrangenaru Vlad;Hong Seong-Wook
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.4 s.181
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    • pp.168-175
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    • 2006
  • This paper presents surface matching algorithms that can be used to reconstruct the surface topography of an object scanned by an AFM. The essence of the algorithms is to match up neighboring images intentionally overlapped with others. Two performance indexes using the correlation coefficient and the sum of the squared differences are introduced. To compensate for the inaccuracy of the coarse stage implemented to AFM, all the six axes including the rotational degrees of freedom are successively matched so as to maximize the coefficients defined. The results show that the proposed algorithms are useful for measurement range extension of AFM. The results also show that a combined use of the two indexes is beneficial for practical cases.

Camera Motion Detection Using Estimation of Motion Vector's Angle (모션 벡터의 각도 성분 추정을 통한 카메라 움직임 검출)

  • Kim, Jae Ho;Lee, Jang Hoon;Jang, Soeun
    • Journal of Korea Multimedia Society
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    • v.21 no.9
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    • pp.1052-1061
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    • 2018
  • In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

Computing Similarities between Segmented Objects in the image for Content-Based Retrieval (내용기반 검색을 위한 분할된 영상객체간 유사도 판별)

  • 유헌우;장동식
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.358-360
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    • 2001
  • 본 논문에서는 내용기반 영상검색중 객체기반검색 방법에 대해 다룬다. 먼저 색상과 질감정보가 동일한 영역을 VQ알고리즘을 이용해 군집화 함으로써 동일한 영역을 추출하는 새로운 영상분할기법을 제안하고, 분할 후에 분할에 사용된 색상과 질감정보, 객체간의 위치정보와 영역크기정보를 가지고 객체간 유사도를 판별하여 영상을 검색한다. 이 때 사용되는 색상의 범위의 몇 개의 주요한 색상으로 표시하기 위해 색상테이블을 사용하고 인간의 인지도에 의해 다시 그룹화 함으로써 계산량과 데이터저장의 효율성을 높인다. 영상검색시에는 질의 영상의 관심객체와 비교대상이 되는 데이터베이스 영상의 여러 객체와의 유사성을 판단하여 영상간의 유사도를 계산하는 일대다 매칭 방법(One Object to Multi Objects Matching)과 질의 영상의 여러 객체와 데이터베이스영상의 여러 객체간의 유사도를 판단하는 다대다 매칭 방법(Multi Objects to Multi Objects Matching)을 제안한다. 또한, 제안된 시스템은 고속검색을 실현하기 위해 주요한 색상값을 키(key)색인화 해서 일치가능성이 없는 영상들은 1차적으로 제거함으로써 검색시간을 줄일 수 있도록 했다.

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Real-Time Object Segmentation of Stereo Matching Image Using the Projection-based Region Merging and the Post Processing of disparity map (변이지도의 후처리 및 프로젝션 기반의 영역병합을 이용한 스테레오 매칭 영상의 실시간 객체분할)

  • Choi, Min-Soo;Shin, Dong-Jin;Han, Dong-Il
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.313-314
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    • 2006
  • Obtained disparity map from the stereo camera by using the several stereo matching algorithms carries lots of noise because of various causes. In our approach, mode filtering and noise elimination technique using the histogram and projection-based region merging methods are adopted for improving the quality of disparity map and image segmentation. The proposed algorithms are implemented in VHDL and the real-time experimentation shows the accurately divided objects.

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Real Object Recognition Based Mobile Augmented Reality Game (현실 객체 인식 기반 모바일 증강현실 게임)

  • Lee, Dong-Chun;Lee, Hun-Joo
    • Journal of Korea Game Society
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    • v.17 no.4
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    • pp.17-24
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    • 2017
  • This paper describes the general process of making augmented reality game for real objects without markers. In this paper, point cloud data created by using slam technology is edited using a separate editing tool to optimize performance in mobile environment. Also, in the game execution stage, a lot of load is generated due to the extraction of feature points and the matching of descriptors. In order to reduce this, optical flow is used to track the matched feature points in the previous input image.

A Study of the Use of step by preprocessing and Graph Cut for the exact depth map (깊이맵 향상을 위한 전처리 과정과 그래프 컷에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
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    • v.10 no.3
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    • pp.99-103
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    • 2011
  • The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using blue edge filter and graph cut algorithm. We do recommend the use of the simple sobel edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). The basic technique is to construct a specialized graph for the energy function to be minimized such that the minimum cut on the graph also minimizes the energy (either globally or locally). This method has the advantage of saving a lot of data. We propose a preprocessing effective stereo matching method based on sobel algorithm which uses blue edge information and the graph cut, we could obtain effective depth map.

Improved image alignment algorithm based on projective invariant for aerial video stabilization

  • Yi, Meng;Guo, Bao-Long;Yan, Chun-Man
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3177-3195
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    • 2014
  • In many moving object detection problems of an aerial video, accurate and robust stabilization is of critical importance. In this paper, a novel accurate image alignment algorithm for aerial electronic image stabilization (EIS) is described. The feature points are first selected using optimal derivative filters based Harris detector, which can improve differentiation accuracy and obtain the precise coordinates of feature points. Then we choose the Delaunay Triangulation edges to find the matching pairs between feature points in overlapping images. The most "useful" matching points that belong to the background are used to find the global transformation parameters using the projective invariant. Finally, intentional motion of the camera is accumulated for correction by Sage-Husa adaptive filtering. Experiment results illustrate that the proposed algorithm is applied to the aerial captured video sequences with various dynamic scenes for performance demonstrations.

A Study of the Use of Step by Preprocessing and Dynamic Programming for the Exact Depth Map (정확한 깊이 맵을 위한 전처리 과정과 다이나믹 프로그래밍에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
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    • v.9 no.3
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    • pp.65-69
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    • 2010
  • The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using nagao filter, octree color quantization and dynamic programming algorithm. we describe methods for performing color quantization on full color RGB images, using an octree data structure. This method has the advantage of saving a lot of data. We propose a preprocessing stereo matching method based on Nagao-filter algorithm using color information. using the nagao filter, we could obtain effective depth map and using the octree color quantization, we could reduce the time of computation.

Real-time Multi-Objects Recognition and Tracking Scheme (실시간 다중 객체 인식 및 추적 기법)

  • Kim, Dae-Hoon;Rho, Seung-Min;Hwang, Een-Jun
    • Journal of Advanced Navigation Technology
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    • v.16 no.2
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    • pp.386-393
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    • 2012
  • In this paper, we propose an efficient multi-object recognition and tracking scheme based on interest points of objects and their feature descriptors. To do that, we first define a set of object types of interest and collect their sample images. For sample images, we detect interest points and construct their feature descriptors using SURF. Next, we perform a statistical analysis of the local features to select representative points among them. Intuitively, the representative points of an object are the interest points that best characterize the object. in addition, we make the movement vectors of the interest points based on matching between their SURF descriptors and track the object using these vectors. Since our scheme treats all the objects independently, it can recognize and track multiple objects simultaneously. Through the experiments, we show that our proposed scheme can achieve reasonable performance.

An Object Tracking Method for Studio Cameras by OpenCV-based Python Program (OpenCV 기반 파이썬 프로그램에 의한 방송용 카메라의 객체 추적 기법)

  • Yang, Yong Jun;Lee, Sang Gu
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.1
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    • pp.291-297
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    • 2018
  • In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.