• 한국통신학회논문지
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• 제29권8C호
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• pp.1133-1141
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• 2004

비디오 데이터를 효율적으로 처리하기 위해서는 비디오 데이터가 가지고 있는 내용에 대한 정보를 데이터베이스에 저장하고 사용자들의 다양한 질의를 처리할 수 있는 의미기반 검색 기법이 요구된다. 본 논문에서는 주석기반 검색과 특징기반 검색을 이용하여 대용량의 비디오 데이터에 대한 사용자의 다양한 의미검색을 지원하는 에이전트 기반에서의 자동화되고 통합된 비디오 의미기반 검색 시스템을 제안한다. 사용자의 기본적인 질의와 질의에 의해 추출된 키 프레임의 이미지를 선택함으로써 에이전트는 추출된 키 프레임의 주석에 대한 의미를 더욱 구체화시킨다. 또한, 사용자에 의해 선택된 키 프레임은 질의 이미지가 되어 제안하는 특징기반 검색기법을 통해 가장 유사한 키 프레임을 검색한다. 설계하고 구현한 시스템은 실험을 통한 성능평가에서 90% 이상의 높은 정확도를 보였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.683-688
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• 2008

The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user's individual preference.

• 한국도서관정보학회지
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• 제31권1호
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• pp.229-258
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• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.

• 한국도서관정보학회지
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• 제40권3호
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• pp.367-387
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• 2009

유사 문헌 검색 시스템은 추출된 색인어 중에서 어떤 것을 선택하는가에 따라 검색 결과에 많은 차이점이 발생한다. 본 연구에서는 추출된 후보 색인어의 선정의 오류를 최소한으로 하는 방법을 제공한다. 본 연구에서는 유사문헌에서 추출된 후보 색인어들을 이용하여 인접한 단어들의 정보와 추출된 키워드 주제어 정보를 이용하였다. 그리고 관련 저자들 정보와 검색 결과의 재순위화 방법을 이용하여 보다 정확도가 높은 유사 문헌 검색 시스템을 개발하였다. 본 논문에서는 과학기술 학회마을 데이터베이스를 이용하여 실험하였다. 실험과 사용자 평가를 통해서 유사 문헌 검색 시스템의 성능을 입증하였다.

• 한국문헌정보학회지
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• 제47권1호
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• pp.39-55
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• 2013

It is a difficult problem to use keyword retrieval for low-quality Korean document images because these include adjacent characters that are connected. In addition, images that are created from various fonts are likely to be distorted during acquisition. In this paper, we propose and test a keyword retrieval system, using a support vector machine (SVM) for the retrieval of low-quality Korean document images. We propose a keyword retrieval method using an SVM to discriminate the similarity between two word images. We demonstrated that the proposed keyword retrieval method is more effective than the accumulated Optical Character Recognition (OCR)-based searching method. Moreover, using the SVM is better than Bayesian decision or artificial neural network for determining the similarity of two images.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2006년도 추계학술발표대회
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• pp.19-22
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• 2006

In this paper we present a vision based place recognition method which uses Bayesian method with feed back of image retrieval. Both Bayesian method and image retrieval method are based on interest features that are invariant to many image transformations. The interest features are detected using Harris-Laplacian detector and then descriptors are generated from the image patches centered at the features' position in the same manner of SIFT. The Bayesian method contains two stages: learning and recognition. The image retrieval result is fed back to the Bayesian recognition to achieve robust and confidence. The experimental results show the effectiveness of our method.

• 한국멀티미디어학회논문지
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• 제8권7호
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• pp.906-915
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• 2005

본 논문에서는 영상검색 방법의 하나인 내용에 기반을 둔 검색방법으로 순차영역분할과 투영정보를 이용 한 영상검색 방법을 제안한다. 제안한 방법은 순차 분할된 영역의 색상평균값과 각 영역의 투영정보를 이용한 방법으로 영상의 공간정보와 컬러정보를 효과적으로 결합한 방법이다. 실험결과 제안한 방법이 기존의 방법 보다 검색효율이 $11.6\%$ 증가됨을 알 수 있었다. 또한 영상의 밝기변화, 회전, 카메라의 위치 및 확대, 축소에 따른 영상의 공간변화에도 매우 강인한 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1403-1417
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• 2019

With the rapid growth of multimedia data, research on cross-media feature learning has significance in many applications, such as multimedia search and recommendation. Existing methods are sensitive to noise and edge information in multimedia data. In this paper, we propose a semi-supervised method for cross-media feature learning by means of $L_{2,q}$ norm to improve the performance of cross-media retrieval, which is more robust and efficient than the previous ones. In our method, noise and edge information have less effect on the results of cross-media retrieval and the dynamic patch information of multimedia data is employed to increase the accuracy of cross-media retrieval. Our method can reduce the interference of noise and edge information and achieve fast convergence. Extensive experiments on the XMedia dataset illustrate that our method has better performance than the state-of-the-art methods.

• 한국도서관정보학회지
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• 제18권
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• pp.91-138
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• 1991

The paper describes the application areas of the hypertext and the relevance of hypertext principles to the information retrieval system. As to the techniques of the hypertext information retrieval the various navigation method including a guided tour, a history list, a browser, a book-mark, etc. are discussed. The query system is considered as the other technique to be integrated into the hypertext system for the enhancement of the interactive function of the information retrieval. Based on the theoretical background, a conceptual model of hypertext information retrieval system was constructed using GUIDE which was developed by P.J. Brown of Kent University. 16 bibliographic records from LISA of 1991(June) were used for the illustration of the basic operation of the system. Though the study could not reach the implementation level due to the absolute constraints of the time and experimental environments, further efforts will continue to develop a prototype system of a hypertext information retrieval. A few conclusions can be derived from the study : (1) The integration of the hypertext into the information retrieval system can be justified by permitting the end-users to have much stronger and more flexible interaction with the system. (2) The more the degree of the sofistication of the existing information retrieval system is the more the possibility of the development of an effective and user-oriented information retrieval system will be greater by integrating guide as a front end system to the underlying software. (3) The deep knowledge about the functions of information retrieval which can be enhanced by the hypertext could be acquired by the information retrieval specialists.

• Journal of Information Processing Systems
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• 제9권3호
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.