• Title, Summary, Keyword: matching

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Extraction of Characteristic Information for Image Matching (영상매칭을 위한 특성정보 추출)

  • 이동천;염재홍;김정우;이용욱
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • pp.171-176
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    • 2004
  • Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

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Probabilistic Model for Performance Analysis of a Heuristic with Multi-byte Suffix Matching

  • Choi, Yoon-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.4
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    • pp.711-725
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    • 2013
  • A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

Effective Sonar Grid map Matching for Topological Place Recognition (위상학적 공간 인식을 위한 효과적인 초음파 격자 지도 매칭 기법 개발)

  • Choi, Jin-Woo;Choi, Min-Yong;Chung, Wan-Kyun
    • The Journal of Korea Robotics Society
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    • v.6 no.3
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    • pp.247-254
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    • 2011
  • This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment.

Relaxation Matching Algorithm Based on Global Structure Constraint Satisfaction (전역 구조 구속 조건에 기초한 Relaxation Matching 알고리즘)

  • Chul, Hur;Jeon, Yang-Bae;Kim, Seung-Min;Kim, Sang-Bong
    • Proceedings of the KSME Conference
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    • pp.706-711
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    • 2001
  • This paper represents a relaxation matching algorithm based on global structure constraint satisfaction. Relaxation matching algorithm is a conventional approach to the matching problem. However, we confronted some problems such as null-matching and multi-matching problems by just using the relaxation matching technique. In order to solve the problems, in this paper, the matching problem is regarded as constraint satisfaction problem, and a relaxation matching algorithm is proposed based on global structure constraint satisfaction. The proposed algorithm is applied a landslide picture to show the effectiveness. When the algorithm is processed at landslide inspecting and monitoring system, motion parameters such as displacement area and its direction are computed. Once movement is recognized, displacements are estimated graphically with statistical amount in the image plane. Simulation has been done to prove the proposed algorithm by using time-sequence image of landslide inspection and monitoring system.

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Efficient 1:N Fingerprint Matching Algorithm using Matching Score Distribution (매칭 점수 분포를 이용한 효율적인 1:N 지문 매칭 알고리듬)

  • Kim, Kyoung-Min;Park, Joong-Jo;Lee, Buhm;Go, Young-Jin;Jung, Soon-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.3
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    • pp.208-217
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    • 2012
  • This paper presents two adaptive fingerprint matching methods. First, we experiment an adaptive threshold selection of 1:N matching system in order to raise the reliability of the matching score. Second, we propose a adaptive threshold selection using fitting algorithm for high speed matching. The experiment was conducted on the NITZEN database, which has 5247 samples. Consequently, this paper shows that our suggested method can perform 1.88 times faster matching speed than the bidirectional matching speed. And, we prove that FRR of our suggested method decreases 1.43 % than that of the unidirectional matching.

Development of A New Patch-Based Stereo Matching Algorithm for Extraction of Digiral Elevation Model from Satellite Imagery (위성영상으로부터 수치표고모형 추출을 위한 새로운 정합구역의 비선형 최소자승 영상정합 알고리즘 개발)

  • 김태정;이흥규
    • Korean Journal of Remote Sensing
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    • v.13 no.2
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    • pp.121-132
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    • 1997
  • This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

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Edge Segment-Based Stereo Matching with Variable Matching Weights (가변 정합 가중치를 이용한 에지 선소 기반 스테레오 정합)

  • Shon, Hong-Rak;Kim, Hyong-Suk
    • Proceedings of the KIEE Conference
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    • pp.2225-2227
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    • 1998
  • An efficient stereo matching method with variable matching weights is proposed. The edge segment-based stereo matching has been shown to be efficient method. The method includes 5 matching factor with different weights. The ordinary matching weights are not always adequate for every image. Employing different weight sets depending on the complexity shows better matching performance. In this paper, an evaluation criterion for complexity is suggested and the experimental results with the proposed method is shown.

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Stereo Matching using Dynamic Programming in Scale-Space (스케일 공간에서 동적 계획을 이용한 스테레오 정합)

  • 최우영;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.8
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    • pp.44-53
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    • 1992
  • In this paper, a matching method is proposed to improve the correct matching rate in stereo correspondence matching in which the fingerprint of zero-crossing points on the scale-space is used as the robust matching feature. The dynamic programming, which is appropriate for the fingerprint feature, is introduced for correspondence matching. We also improve the matching rate by using the post-processing for correcting mismatched points. In simulation, we apply the proposed algorithm to the synthetic and real images and obtain good matching results.

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Bi-directional Fuzzy Matching Algorithm (양방향 퍼지 매칭 알고리즘: 취업정보 적용)

  • Kim, Hyoung-Rae;Jeong, In-Soo
    • Journal of Internet Computing and Services
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    • v.12 no.3
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    • pp.69-76
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    • 2011
  • Matching customers becomes the key function in on-line mediate services. There are two matching methods: one-directional matching that requires requests from one side(e,g., information searching), bi-directional matching that considers requests from both sides. Previous bi-directional matching has difficulties of getting the interests explicitly and service collapse problems when the opposite side do not put responding interests. This paper attempts to automate the inputs of interests for bi-directional matching by calculating the interests with fuzzy matching algorithm for optimization. The results of the proposed Bi-directional Fuzzy Matching(BDFM) algorithm told that the job placement accuracy of employment information matching results is over 95%. And, BDFM gives statically significant positive effect for motivating the employment activities when analyzed the effect after completing the implementation.

GPU-Based Optimization of Self-Organizing Map Feature Matching for Real-Time Stereo Vision

  • Sharma, Kajal;Saifullah, Saifullah;Moon, Inkyu
    • Journal of information and communication convergence engineering
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    • v.12 no.2
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    • pp.128-134
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    • 2014
  • In this paper, we present a graphics processing unit (GPU)-based matching technique for the purpose of fast feature matching between different images. The scale invariant feature transform algorithm developed by Lowe for various feature matching applications, such as stereo vision and object recognition, is computationally intensive. To address this problem, we propose a matching technique optimized for GPUs to perform computations in less time. We optimize GPUs for fast computation of keypoints to make our system quick and efficient. The proposed method uses a self-organizing map feature matching technique to perform efficient matching between the different images. The experiments are performed on various image sets to examine the performance of the system under varying conditions, such as image rotation, scaling, and blurring. The experimental results show that the proposed algorithm outperforms the existing feature matching methods, resulting in fast feature matching due to the optimization of the GPU.