• 제목/요약/키워드: model matching problems

검색결과 102건 처리시간 0.027초

면 법선 영상 기반형 3차원 물체인식에서의 새로운 매칭 기법 (A New Matching Strategy for SNI-based 3-D Object Recognition)

  • 박종훈;최종수
    • 전자공학회논문지B
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    • 제30B권7호
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    • pp.59-69
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    • 1993
  • In this paper, a new matching strategy for 3-D object recognition, based on the Surface Normal Images (SNIs), is proposed. The matching strategy using the similarity decision function [9,10] lost the efficiency and the reliability of matching, because all features of models within model base must be compared with the scene object features, and the weights of the attributes of features is given by heuristic manner. However, the proposed matching strategy can solve these problems by using a new approach. In the approach, by searching the model base, a model object whose features are fully matched with the features of sceme object is selected. In this paper, the model base is constructed for the total 26 objects, and systhetic and real range images are used in the test of the system operation. Experimental result is performed to show the possibility that this strategy can be effectively used for the SNI based recognition.

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유전자 알고리즘을 이용한 물체인식을 위한 특징점 일치에 관한 연구 (A Study on Feature Points matching for Object Recognition Using Genetic Algorithm)

  • 이진호;박상호
    • 한국정보처리학회논문지
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    • 제6권4호
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    • pp.1120-1128
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    • 1999
  • 모델을 이용한 물체인식을 모델영상들과 입력영상 간의 그래프 매칭과정으로 정의하였다. 본 논문에서는 그래프 매칭 문제를 최적화문제로 모델링하였고 최적화 문제해결을 위하여 유전자 알고리즘을 제안하였다. 이를 위하여 적합성함수, 자료구조, 유전연산자들이 개발되었다. 제안된 유전자 알고리즘이 이차원 영상에서 부분적으로 겹쳐진 물제들을 인식하기 위한 모델영상과 입력영상 간의 특징 점들을 일치시킴을 시뮬레이션을 통하여 보였다. 제안된 방법의 성능을 신경회로망을 이용한 방법과 비교하였다.

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로버스트 회귀모형을 이용한 자료결합방법 (Statistical Matching Techniques Using the Robust Regression Model)

  • 전명식;정시송;박혜진
    • 응용통계연구
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    • 제21권6호
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    • pp.981-996
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    • 2008
  • 서로 다른 출처로부터 얻어진 데이터 파일들을 하나의 데이터 파일로 만드는 통계적 자료결합방법은 공통변수와 서로 다른 고유변수를 포함하여 변수들 간에 존재하는 관련성에 대해 살펴볼 수 있다. Robin (1986)이 제안한 일반회귀모형의 예측값을 이용한 통계적 결합방법은 자료에 대한 다변량 정규성을 가정하기 때문에 이 가정을 위반하는 자료를 이용하는 것은 많은 문제를 수반한다. 본 연구는 제공파일의 고유변수에 모분포를 반영하지 못하는 특이점이 존재하는 경우, 일반회귀모형을 이용한 통계적 결합방법의 대안으로 로러스트 회귀추정방법을 이용한 자료결합방법을 제안하였다. 나아가 로버스트 회귀모형을 이용한 결합방법과 일반회귀모형을 이용한 결합방법에서의 상관관계 및 결정계수 보존에 관한 성능을 비교하기 위하여 모의실험을 수행하였다.

모델차수축소법을 이용한 효율적인 진동해석 (Efficient Vibration Simulation Using Model Order Reduction)

  • 한정삼
    • 대한기계학회논문집A
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    • 제30권3호
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    • pp.310-317
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    • 2006
  • Currently most practical vibration and structural problems in automotive suspensions require the use of the finite element method to obtain their structural responses. When the finite element model has a very large number of degrees of freedom the harmonic and dynamic analyses are computationally too expensive to repeat within a feasible design process time. To alleviate the computational difficulty, this paper presents a moment-matching based model order reduction (MOR) which reduces the number of degrees of freedom of the original finite element model and speeds up the necessary simulations with the reduced-size models. The moment-matching model reduction via the Arnoldi process is performed directly to ANSYS finite element models by software mor4ansys. Among automotive suspension components, a knuckle is taken as an example to demonstrate the advantages of this approach for vibration simulation. The frequency and transient dynamic responses by the MOR are compared with those by the mode superposition method.

PCB 검사를 위한 개선된 통계적 그레이레벨 모델 (Improved Statistical Grey-Level Models for PCB Inspection)

  • 복진섭;조태훈
    • 반도체디스플레이기술학회지
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    • 제12권1호
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    • pp.1-7
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    • 2013
  • Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

동적계획법을 이용한 컬러 스테레오 정합 (Color Stereo Matching Using Dynamic Programming)

  • 오종규;이찬호;김종구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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    • pp.747-749
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    • 2000
  • In this paper, we proposed color stereo matching algorithm using dynamic programming. The conventional gray stereo matching algorithms show blur at depth discontinuities and non-existence of matching pixel in occlusion lesions. Also it accompanies matching error by lack of matching information in the untextured region. This paper defines new cost function makes up for the problems happening in conventional gray stereo matching algorithm. New cost function contain the following properties. I) Edge points are corresponded to edge points. ii) Non-edge points are corresponded to non-edge points. iii) In case of exiting the amount of edges, the cost function has some weight in proportion to path distance. Proposed algorithm was applied in various images obtained by parallel camera model. As the result, proposed algorithm showed improved performance in the aspect of matching error and processing in the occlusion region compared to conventional gray stereo matching algorithms.

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Development of a link extrapolation-based food web model adapted to Korean stream ecosystems

  • Minyoung Lee;Yongeun Kim;Kijong Cho
    • 환경생물
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    • 제42권2호
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    • pp.207-218
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    • 2024
  • Food webs have received global attention as next-generation biomonitoring tools; however, it remains challenging because revealing trophic links between species is costly and laborious. Although a link-extrapolation method utilizing published trophic link data can address this difficulty, it has limitations when applied to construct food webs in domestic streams due to the lack of information on endemic species in global literature. Therefore, this study aimed to develop a link extrapolation-based food web model adapted to Korean stream ecosystems. We considered taxonomic similarity of predation and dominance of generalists in aquatic ecosystems, designing taxonomically higher-level matching methods: family matching for all fish (Family), endemic fish (Family-E), endemic fish playing the role of consumers (Family-EC), and resources (Family-ER). By adding the commonly used genus matching method (Genus) to these four matching methods, a total of five matching methods were used to construct 103 domestic food webs. Predictive power of both individual links and food web indices were evaluated by comparing constructed food webs with corresponding empirical food webs. Results showed that, in both evaluations, proposed methods tended to perform better than Genus in a data-poor environment. In particular, Family-E and Family-EC were the most effective matching methods. Our model addressed domestic data scarcity problems when using a link-extrapolation method. It offers opportunities to understand stream ecosystem food webs and may provide novel insights into biomonitoring.

이동로봇주행을 위한 영상처리 기술

  • 허경식;김동수
    • 전자공학회지
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    • 제23권12호
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    • pp.115-125
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    • 1996
  • This paper presents a new algorithm for the self-localization of a mobile robot using one degree perspective Invariant(Cross Ratio). Most of conventional model-based self-localization methods have some problems that data structure building, map updating and matching processes are very complex. Use of a simple cross ratio can be effective to the above problems. The algorithm is based on two basic assumptions that the ground plane is flat and two locally parallel sloe-lines are available. Also it is assumed that an environmental map is available for matching between the scene and the model. To extract an accurate steering angle for a mobile robot, we take advantage of geometric features such as vanishing points. Feature points for cross ratio are extracted robustly using a vanishing point and intersection points between two locally parallel side-lines and vertical lines. Also the local position estimation problem has been treated when feature points exist less than 4points in the viewed scene. The robustness and feasibility of our algorithms have been demonstrated through real world experiments In Indoor environments using an indoor mobile robot, KASIRI-II(KAist Simple Roving Intelligence).

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A self-localization algorithm for a mobile robot using perspective invariant

  • Roh, Kyoung-Sig;Lee, Wang-Heon;Kweon, In-So
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.920-923
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    • 1996
  • This paper presents a new algorithm for the self-localization of a mobile robot using perspective invariant(Cross Ratio). Most of conventional model-based self-localization methods have some problems that data structure building, map updating and matching processes are very complex. Use of the simple cross ratio can be effective to the above problems. The algorithm is based on two basic assumptions that the ground plane is flat and two parallel walls are available. Also it is assumed that an environmental map is available for matching between the scene and the model. To extract an accurate steering angle for a mobile robot, we take advantage of geometric features such as vanishing points(V.P). Point features for computing cross ratios are extracted robustly using a vanishing point and the intersection points between floor and the vertical lines of door frames. The robustness and feasibility of our algorithms have been demonstrated through experiments in indoor environments using an indoor mobile robot, KASIRI-II(KAist SImple Roving Intelligence).

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아날로지를 기반으로 한 객체모델의 재사용 (Analogy-based Reuse of Object Model)

  • 배제민
    • 정보처리학회논문지D
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    • 제14D권6호
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    • pp.665-674
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    • 2007
  • 소스 코드 재사용은 다른 개발자에 의해 만들어진 코드를 정확하게 이해하거나 검색하기 어렵다는 점에서 몇 가지 제한점을 갖는다. 이러한 문제점을 해결하기 위해서 소스코드 자체보다는 분석 및 설계 정보를 재사용하는 것이 가능해야 한다. 이에 본 논문은 객체 모델 및 패턴을 재사용하기 위해 필요한 analogical 매칭 기법을 제안한다. 그리고_ 객체 모델과 디자인 패턴을 재사용 컴포넌트로서 저장할 수 있도록 표현하는 방법을 제안한다. 즉, 재사용 라이브러리에 저장된 유사 컴포넌트를 검색하는 analogical 매칭 함수와 매칭을 지원할 수 있는 라이브러리 구조 및 재사용 컴포넌트의 라이브러리내 표현 방법에 대해 기술하였다.