• 제어로봇시스템학회논문지
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• 제18권11호
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• pp.1027-1033
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• 2012

Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries, but the traditional semantic matching methods based on the ontology tree have three weaknesses which may lead to many false matches, causing the falling precision. In order to improve the matching precision and the recall of the information retrieval, this paper proposes a multi-agent improved semantic similarity matching algorithm based on the ontology tree, which can avoid the considerable computation redundancies and mismatching during the entire matching process. The results of the experiments performed on our algorithm show improvements in precision and recall compared with the information retrieval techniques based on the traditional semantic similarity matching methods.

• 정보보호학회논문지
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• 제25권3호
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• pp.595-602
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• 2015

디지털 포렌식 분야가 직면한 과제 중 하나는 대량의 데이터를 어떻게 효율적으로 처리할 것인가이다. 디지털 객체 간의 유사성을 빠르게 식별하기 위해 신뢰성 있는 다양한 근사 매칭 알고리즘이 계속하여 제시되어왔다. 하지만 알고리즘만으로 문자열의 의미적 유사성을 식별하면 많은 오탐을 보여 오히려 그 실효성을 끌어내리고 있다. 이와 같은 문제점을 해결하고자 근사 매칭 대상의 전처리 과정을 추가하여, 알고리즘 자체의 신뢰성은 유지하면서 유사도 탐지 정확성을 더 높일 수 있는 방법을 제시한다. 본 논문에서는 의미적 유사성을 식별하고자 eml과 hwp 세트를 가지고 sdhash로 실험하였으며, 실험 결과를 이용하여 그 효과성을 검증한다.

• 한국정보통신학회논문지
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• 제24권11호
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• pp.1424-1430
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• 2020

본 논문에서는 영상에 존재하는 잡음의 특성을 고려하여 AWGN을 제거하기 위한 알고리즘을 제안한다. 제안한 알고리즘은 출력 계산을 위해 블록 매칭을 사용하였으며, 센터 마스크와 매칭 마스크의 유사도 판별하여 추정치를 계산한다. 필터의 출력은 추정치와 입력 화소값을 가감하여 계산하며, 센터 마스크의 표준 편차와 잡음 상수에 따라 가중치를 부여하여 최종 출력을 구한다. 제안하는 알고리즘을 평가하기 위해 기존 방법들과 비교하여 시뮬레이션하였으며, 확대영상 및 PSNR비교를 통해 분석하였다. 제안한 알고리즘은 잡음의 영향을 최소화하였으며, 영상의 중요 특성을 보존하며 효율적으로 잡음을 제거하는 성능을 보였다.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• 한국멀티미디어학회논문지
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• 제22권12호
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• pp.1404-1414
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• 2019

Educational books commonly use some copyrighted images with various kinds of deformation for helping students understanding. When using several copyrighted images made by merging or editing distortion in legal, we need to pay a charge to original copyright holders for each image. In this paper, we propose an efficient matching algorithm by separating each copyrighted image with the merged and edited type including rotation, illumination change, and change of size. We use the Oriented FAST and Rotated BRIEF (ORB) method as a basic feature matching scheme. To improve the matching accuracy, we design a new MIN-MAX similarity in matching stage. With the distorted dataset, the proposed method shows up-to 97% of precision in experiments. Also, we demonstrate that the proposed similarity measure also outperforms compared to other measure which is commonly used.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권8호
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• pp.335-343
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• 2002

A segment matching algorithm in stereo vision via the fusion of multiple features on long edge segments is proposed. One problem of the previous segment matching algorithm is the similarity among the segments caused from its short length. In the proposed algorithm, edges are composed of longer segments which are obtained by breaking the edges only at the locations with distinguished changes of the shape. Such long segments can contain extra features such as curvature ratio and length of segments which could not be included in shorter ones. Use of such additional features enhances the matching accuracy significantly To fuse multiple features for matching, weighting value determination algorithm which is computed according to the degree of the contribution of each factor is proposed. The stereo matching simulations with the proposed algorithm are done about various images and their results are included.

• International Journal of Contents
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• 제9권2호
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• pp.1-7
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• 2013

This paper proposes an efficient matching algorithm based on ASIFT (Affine Scale-Invariant Feature Transform) which is fully invariant to affine transformation. In our approach, we proposed a method of reducing similar measure matching cost and the number of outliers. First, we combined the Manhattan and Chessboard metrics replacing the Euclidean metric by a linear combination for measuring the similarity of keypoints. These two metrics are simple but really efficient. Using our method the computation time for matching step was saved and also the number of correct matches was increased. By applying an Optimized Random Sampling Algorithm (ORSA), we can remove most of the outlier matches to make the result meaningful. This method was experimented on various combinations of affine transform. The experimental result shows that our method is superior to SIFT and ASIFT.

• 한국정보과학회논문지:정보통신
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• 제36권1호
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• pp.50-56
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• 2009

본 논문에서는 P2P 네트워크 환경에서 유사한 특성을 가진 다른 노드(node)를 찾아 추천자(recommender) 그룹을 형성하고 유지하는 새로운 알고리즘을 제안한다. 두 노드의 유사한 특성을 비교하기 위해 본 논문에서는 두 노드의 특성값(characteristic value. 이하 CV)을 이용한 적합도 검사(fitness evaluation)를 사용하여 유사도(similarity)를 확인한다. 유사도의 크기가 작을수록 두 노드는 매우 유사한 특성을 가지게 된다. 또한, 본 논문에서 제안하는 GORGFM(Globally Optimal Recommender Group Formation and Maintenance) 알고리즘은 최단 기간 내에 최적의 추천자 그룹을 형성하고 사용자의 선호도 변화에 대응할 수 있는 알고리즘이다. GORGFM 알고리즘을 평가하기 위해 본 논문에서는 매칭율(matching rate)과 얼마나 빠르고 정확하게 추천자 그룹을 형성하는가에 대해 시뮬레이션 한다. GORGFM 알고리즘은 네트워크에서뿐만 아니라 인터넷상에서 컨텐츠(contents) 검색 등과 같이 적합도 함수(fitness function)를 이용할 수 있는 모든 시스템에 적용할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.98.2-98
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• 2002

$\textbullet$ Omnidirectional feature matching $\textbullet$ SVD-based matching algorithm $\textbullet$ Using SSD instead of the zero-mean correlation $\textbullet$ The similarity with the Gaussian weighted $\textbullet$ Low computational cost $\textbullet$ It describes the similarity of the matched pairs in omnidirectional images.

• 제어로봇시스템학회논문지
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• 제16권8호
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• pp.744-750
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• 2010

To segment instances of vehicle classes in a sparse stereo-matching data set, this paper presents an algorithm for clustering based on DP (Dynamic Programming). The algorithm is agglomerative: it begins with each element in the set as a separate cluster and merges them into successively larger clusters according to similarity of two clusters. Here, similarity is formulated as a cost function of DP. The proposed algorithm is proven to be effective by experiments performed on various images acquired by a moving vehicle.