• Title/Summary/Keyword: Matching Methods

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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.

Efficient two-step pattern matching method for off-line recognition of handwritten Hangul (필기체 한글의 오프라인 인식을 위한 효과적인 두 단계 패턴 정합 방법)

  • 박정선;이성환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.4
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    • pp.1-8
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    • 1994
  • In this paper, we propose an efficient two-step pattern matching method which promises shape distortion-tolerant recognition of handwritten of handwritten Hangul syllables. In the first step, nonlinear shape normalization is carried out to compensate for global shape distortions in handwritten characters, then a preliminary classification based on simple pattern matching is performed. In the next step, nonlinear pattern matching which achieves best matching between input and reference pattern is carried out to compensate for local shape distortions, then detailed classification which determines the final result of classification is performed. As the performance of recognition systems based on pattern matching methods is greatly effected by the quality of reference patterns. we construct reference patterns by combining the proposed nonlinear pattern matching method with a well-known averaging techniques. Experimental results reveal that recognition performance is greatly improved by the proposed two-step pattern matching method and the reference pattern construction scheme.

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Determination of Aquifer Parameters by the Improved Slope-Matching Method (개선된 SM(Slope-Matching) 방법에 의한 대수층의 특성변수 결정)

  • 김민환;오종민;전일권
    • Journal of Soil and Groundwater Environment
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    • v.6 no.4
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    • pp.73-81
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    • 2001
  • With the development of industry and standard of living, the quantity of groundwater consumption has been increasing. For the analysis of groundwater, to determine the hydraulic parameters of aquifer is very important. Various numerical methods have been developed to solve aquifer tests and eliminate the subjectivity of traditional graphical type curve methods. The slope-matching method, which matches the slope of the Theis type curve to the slope of the field data, can be used to numerically solve pump tests for both leaky and nonleaky aquifers. A FORTRAN program on based slope-matching method was developed to obtain the transmissivity, storage coefficient, and leaky factor from pumping test data automatically. Results derived from published data show that the improved slope-matching method gives parameters close to the ones derived by the slope-matching method.

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On-line Signature Verification using Segment Matching and LDA Method (구간분할 매칭방법과 선형판별분석기법을 융합한 온라인 서명 검증)

  • Lee, Dae-Jong;Go, Hyoun-Joo;Chun, Myung-Geun
    • Journal of KIISE:Software and Applications
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    • v.34 no.12
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    • pp.1065-1074
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    • 2007
  • Among various methods to compare reference signatures with an input signature, the segment-to-segment matching method has more advantages than global and point-to-point methods. However, the segment-to-segment matching method has the problem of having lower recognition rate according to the variation of partitioning points. To resolve this drawback, this paper proposes a signature verification method by considering linear discriminant analysis as well as segment-to-segment matching method. For the final decision step, we adopt statistical based Bayesian classifier technique to effectively combine two individual systems. Under the various experiments, the proposed method shows better performance than segment-to-segment based matching method.

IKONOS Stereo Matching with Land Cover Map for DEM Generation

  • Lee, Hyo-Seong;Ahn, Ki-Weon;Park, Byung-Guk;Han, Dong-Yeob
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.580-583
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    • 2007
  • Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

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Improving Bagging Predictors

  • Kim, Hyun-Joong;Chung, Dong-Jun
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.141-146
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    • 2005
  • Ensemble method has been known as one of the most powerful classification tools that can improve prediction accuracy. Ensemble method also has been understood as ‘perturb and combine’ strategy. Many studies have tried to develop ensemble methods by improving perturbation. In this paper, we propose two new ensemble methods that improve combining, based on the idea of pattern matching. In the experiment with simulation data and with real dataset, the proposed ensemble methods peformed better than bagging. The proposed ensemble methods give the most accurate prediction when the pruned tree was used as the base learner.

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Comparison of error rates of various stereo matching methods for mobile stereo vision systems (모바일 스테레오 비전 시스템을 위한 다양한 스테레오 정합 기법의 오차율 비교)

  • Joo-Young, Lee;Kwang-yeob, Lee
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.686-692
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    • 2022
  • In this paper, the matching error rates of modified area-based, energy-based algorithms, and learning-based structures were compared for stereo image matching. Census transform (CT) based on region and life propagation (BP) algorithm based on energy were selected, respectively.Existing algorithms have been improved and implemented in an embedded processor environment so that they can be used for stereo image matching in mobile systems. Even in the case of the learning base to be compared, a neural network structure that utilizes small-scale parameters was adopted. To compare the error rates of the three matching methods, Middlebury's Tsukuba was selected as a test image and subdivided into non-occlusion, discontinuous, and disparity error rates for accurate comparison. As a result of the experiment, the error rate of modified CT matching improved by about 11% when compared with the existing algorithm. BP matching was about 87% better than conventional CT in the error rate. Compared to the learning base using neural networks, BP matching was about 31% superior.

Object matching algorithms using robust hausdorff distance measure (Robust hausdorff 거리 척도를 이용한 물체 정합 알고리듬)

  • 권오규;심동규;박래홍
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.11
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    • pp.93-101
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    • 1997
  • A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

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On Second Order Probability Matching Criterion in the One-Way Random Effect Model

  • Kim, Dal Ho;Kang, Sang Gil;Lee, Woo Dong
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.29-37
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    • 2001
  • In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

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