• 제목/요약/키워드: Content-based information retrieval

검색결과 606건 처리시간 0.024초

내용기반 영상정보 검색기술에 관한 이론적 고찰 (A Study on Content-based Image Information Retrieval Technique)

  • 노진구
    • 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.

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내용기반 이미지 및 비디오 검색 시스템 성능분석에 관한 연구 (A Study on the Performance Analysis of Content-based Image & Video Retrieval Systems)

  • 김성희
    • 한국비블리아학회지
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    • 제15권2호
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    • pp.97-115
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    • 2004
  • 본 논문에서는 먼저 이미지 및 비디오 내용기반 검색 시스템 개념 및 유형을 분석 한 후 현재 상용중인 내용기반 검색시스템 5개를 선정해서 기존의 선행연구 및 각 시스템 홈페이지를 방문하여 성능을 분석 하였다. 그 결과 멀티미디어 정보검색의 효율성을 개선하기 위해서는 내용기반 검색과 주석기반 검색을 병행하는 것이 바람직한 것으로 나타났다.

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멜로디 시퀸스를 이용하는 내용 기반 음악 검색 알고리즘 (A Content-Based Music Retrieval Algorithm Using Melody Sequences)

  • 위조민;구경이;김유성
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (1)
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    • pp.250-252
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    • 2001
  • With the growth in computer and network technologies, some content-based music retrieval systems have been developed. However, their retrieval efficiency does not satisfy user's requirement yet. Of course users hope to have a more efficient and higher precision for music retrieval. In this paper so for these reasons, we Propose an efficient content-based music retrieval algorithm using melodies represented as music sequences. From the experimental result, it is shown that the proposed algorithm has higher exact rate than the related algorithms.

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A Self-selection of Adaptive Feature using DCT

  • Lim, Seung-in
    • 한국컴퓨터정보학회논문지
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    • 제5권3호
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    • pp.215-219
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    • 2000
  • The purpose of this paper is to propose a method to maximize the efficiency of a content-based image retrieval for various kinds of images. This paper discuss the self-adaptivity for the change of image domain and the self-selection of optimal features for query image, and present the efficient method to maximize content-based retrieval for various kinds of images. In this method, a content-based retrieval system is adopted to select automatically distinctive feature patterns which have a maximum efficiency of image retrieval in various kinds of images. Experimental results show that the Proposed method is improved 3% than the method using individual features.

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Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback

  • Mussarat, Yasmin;Muhammad, Sharif;Sajjad, Mohsin;Isma, Irum
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권12호
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    • pp.3149-3165
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    • 2013
  • Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

중복된 칼라 히스토그램과 공간 정보를 이용한 내용 기반 화상 검색 시스템 설계 및 구현 (LDesign and implementation of a content-based image retrieval system using the duplicated color histogram and spatial information)

  • 김철원;최기호
    • 한국통신학회논문지
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    • 제22권5호
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    • pp.889-898
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    • 1997
  • Most general content-based image retrieval techniques use color and texture as retrieval indices. Spatial information is not used to color histogram and color pair based on color retrieval techniques. This paper proposes the selection of a set of representative in the duplicated color histogram, the analysis of spatial information of the selected colors and the image retrieval process based on the duplicated color histogram and spatial information. Two color historgrams for background and object are used in order to decide on color selection in the duplicated color histogram. Spatial information is obtained using a maximum entropy discretization. A retrieval process applies to duplicated color histogram and spatial to retrieve input images and relevant images. As the result of experiment of the image retrieval, improved color his togram and spatial information method hs increased the retrieval effectiveness more the color histogram method and color pair method.

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Interactive Genetic Algorithm for Content-based Image Retrieval

  • Lee, Joo-Young;Cho, Sung-Bae
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.479-484
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    • 1998
  • As technology in a computer hardware and software advances, efficient information retrieval from multimedia database gets highly demanded. Recently, it has been actively exploited to retrieve information based on the stored contents. However, most of the methods emphasize on the points which are far from human intuition or emotion. In order to overcome this shortcoming , this paper attempts to apply interactive genetic algorithm to content-based image retrieval. A preliminary result with subjective test shows the usefulness of this approach.

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영상 검색을 위한 적응적 컴포넌트 분석 시스템 설계 (The Design of Adaptive Component Analysis System for Image Retrieval)

  • 최철;박장춘
    • 한국컴퓨터정보학회논문지
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    • 제9권2호
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    • pp.19-26
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    • 2004
  • 본 논문에서는 내용 기반 영상 검색 시스템(Content Based Image Retrieval System)의 특징 추출(feature extraction)과 분석(analysis)을 위한 방법으로 적응적 컴포넌트 분석(ACA: Adaptive Component Analysis)을 제안하고 있다. 검색을 위해서 영상에서 추출된 특징들은 영상의 도메인(domain)에 따라 적절하게 적용해야만 좋은 검색 결과를 얻을 수 있다. 이러한 조건을 만족시키기 위한 방법으로 본 논문에서는 검색 측정도(retrieval measurement)를 제안하고 있다. ACA는 알고리즘과 시스템적인 관점에서 볼 때, 기존의 내용 기반 영상 검색을 위한 중간 단계라고 할 수 있으며, 검색 속도향상 및 성능 개선에 목표를 두고 있다

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Metadata Processing Technique for Similar Image Search of Mobile Platform

  • Seo, Jung-Hee
    • Journal of information and communication convergence engineering
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    • 제19권1호
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    • pp.36-41
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    • 2021
  • Text-based image retrieval is not only cumbersome as it requires the manual input of keywords by the user, but is also limited in the semantic approach of keywords. However, content-based image retrieval enables visual processing by a computer to solve the problems of text retrieval more fundamentally. Vision applications such as extraction and mapping of image characteristics, require the processing of a large amount of data in a mobile environment, rendering efficient power consumption difficult. Hence, an effective image retrieval method on mobile platforms is proposed herein. To provide the visual meaning of keywords to be inserted into images, the efficiency of image retrieval is improved by extracting keywords of exchangeable image file format metadata from images retrieved through a content-based similar image retrieval method and then adding automatic keywords to images captured on mobile devices. Additionally, users can manually add or modify keywords to the image metadata.

A Semantic Content Retrieval and Browsing System Based on Associative Relation in Video Databases

  • Bok Kyoung-Soo;Yoo Jae-Soo
    • International Journal of Contents
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    • 제2권1호
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    • pp.22-28
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    • 2006
  • In this paper, we propose new semantic contents modeling using individual features, associative relations and visual features for efficiently supporting browsing and retrieval of video semantic contents. And we implement and design a browsing and retrieval system based on the semantic contents modeling. The browsing system supports annotation based information, keyframe based visual information, associative relations, and text based semantic information using a tree based browsing technique. The retrieval system supports text based retrieval, visual feature and associative relations according to the retrieval types of semantic contents.

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