• 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.

• 정보관리학회지
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• 제28권2호
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• pp.135-158
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• 2011

탐색자가 정보 요구를 정보검색시스템에 표현하는 능력은 검색과정의 기본이다. 시각적 예시에 의한 질의는 내용기반 이미지 검색환경에서 질의 표현을 위한 중요한 패러다임이다. 하지만, 이 방법이 질의 구성의 편의성에 있어 얼마나 효과가 있는지에 대한 실험적 입증은 아직 미미하다. 이 연구의 목적은 다양한 정보요구와 효율적이고도 효과적인 시각적 질의 구성을 지원하기 위해 탐색자의 정보요구와 질의 방법 사이에 발생하는 지식 격차를 고려하여 색을 이용한 질의 방식의 사용성을 조사하기 위한 것이다. 본 연구결과를 통하여 색을 이용한 질의 방법이 시각적 질의 구성을 적절히 지원하지 못한다는 것과 탐색자의 정보요구와 검색 패러다임의 표현력 사이에 뚜렷한 불일치가 있다는 것을 알 수 있다.

• 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.

• Journal of information and communication convergence engineering
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• 제22권1호
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• pp.56-63
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• 2024

Despite the rapid strides in content-based image retrieval, a notable disparity persists between the visual features of images and the semantic features discerned by humans. Hence, image retrieval based on the association of semantic similarities recognized by humans with visual similarities is a difficult task for most image-retrieval systems. Our study endeavors to bridge this gap by refining image semantics, aligning them more closely with human perception. Deep learning techniques are used to semantically classify images and retrieve those that are semantically similar to personalized images. Moreover, we introduce a keyword-based image retrieval, enabling automatic labeling of images in mobile environments. The proposed approach can improve the performance of a mobile device with limited resources and bandwidth by performing retrieval based on the visual features and keywords of the image on the mobile device.

• 정보통신설비학회논문지
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• 제10권3호
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• pp.103-109
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• 2011

With the growing popularity of digital video applications, those areas of the efficient transmit, storage management, and search technology for video data are emerging as an important core technology. To be an effective video indexing system, users need to be able to find the video segments that they want. Unfortunately, video data is difficult to manage because of its unstructured data type and large volume with linear forms. This paper proposes a shot verification using visual rhythm and video retrieval system. The shot verification is designed to detect a segment from video easily and quickly, known as shot boundaries, just by changing the visual rhythm without playing the image. Therefore, this can decrease the false detected shots and generate the unidentified shots and key frames. The retrieval system is constructed in terms of visual descriptor from the list of MPEG-7. The effectiveness of the proposed shot verification process and video retrieval system is demonstrated.

• 정보관리연구
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• 제42권3호
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• pp.71-94
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• 2011

시각적 실례에 의한 질의는 내용기반 이미지 검색 환경에서 질의 표현을 위한 중요한 질의 패러다임이다. 이미지 및 스케치에 의한 질의는 질의표현을 가능하게 하는 방법으로서 오랫동안 알려졌다. 하지만 이 방법이 질의를 쉽게 작성하는 데 얼마나 도움을 주는지에 대한 효율성에 대한 실험적 입증은 아직 미미하다. 정보검색시스템에 표현하는 탐색자의 능력은 검색과정의 기본이다. 이 연구의 목적은 탐색자의 정보 문제와 효율적이고도 효과적인 시각적 질의 작성을 지원하기 위해 필요한 질의 방법들 간의 지식 격차의 원인이 되는 다양한 정보 요구를 지원하는 데 있어서 유용성 실험을 통해 이미지에 의한 질의와 스케치방법에 의한 질의 조사하기 위함이었다. 본 연구 결과는 이미지에 의한 질의가 시각적 질의 작성에 실행 가능한 접근방식임을 제시한다. 반면에, 본 연구결과를 통해 탐색자의 정보 문제와 시각적인 질의 작성에 도움을 주는 스케치 패러다임에 의한 질의표현 능력 간에 상당한 불일치가 있다는 것을 알 수 있다. 효율(시간)과 유효성(오류)에 초점을 둔 유용성 실험결과와 이용자의 만족도는 큰 차이점이 있다고 보여준다(p<0.001). 이는 다음 세 가지 측정(시간, 오류, 이용자의 만족도)에 대한 두 가지 질의 방식(이미지에 의한 질의, 스케치에 의한 질의) 사이에서 나타난 시간(Z=-3.597, p<0.001), 오류(Z=-3.317, p<0.001), 그리고 만족도(Z=-10.223, p<0.001)에서 드러난다. 본 연구결과는 또한 질의도구를 참가자가 인지하는 유용성에 큰 차이가 있다는 것을 보여준다(Z=-4.672, p<0.001).

• Journal of Computing Science and Engineering
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• 제6권2호
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• pp.168-177
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• 2012

The search for relevant and actionable information is a key to achieving clinical and research goals in biomedicine. Biomedical information exists in different forms: as text and illustrations in journal articles and other documents, in images stored in databases, and as patients' cases in electronic health records. This paper presents ways to move beyond conventional text-based searching of these resources, by combining text and visual features in search queries and document representation. A combination of techniques and tools from the fields of natural language processing, information retrieval, and content-based image retrieval allows the development of building blocks for advanced information services. Such services enable searching by textual as well as visual queries, and retrieving documents enriched by relevant images, charts, and other illustrations from the journal literature, patient records and image databases.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3806-3825
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• 2016

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L₂ distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

• 반도체디스플레이기술학회지
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• 제13권2호
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.