• The Journal of the Acoustical Society of Korea
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• 제26권3E호
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• pp.74-79
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• 2007

In this paper, we report our recent work on a indexing and retrieval system of broadcast news using audio content analysis. Key issues addressed in this work are two major parts of the audio indexing system: anchorperson detection based on audio segmentation, and phone-based spoken document retrieval, developed in the framework of the emerging MPEG-7 standard. Experiments are conducted on a database of Britisch broadcast news videos. We discuss the development of the retrieval system, and the evaluation of each part and the retrieval system.

• 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

• 한국컴퓨터정보학회지
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• 제12권1호
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• pp.9-19
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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 속도 향상 및 성능 개선에 목표를 두고 있다.

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.

• 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.

• 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.

• 산업경영시스템학회지
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• 제27권3호
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• pp.59-65
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• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• 대한전자공학회논문지SP
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• 제43권2호
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• pp.57-64
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• 2006

본 논문에서는 해마신경망(HCNN:HippoCampal Neural Network)을 이용하여 사용자 친화적인 객체 기반 멀티미디어 검색시스템을 제안한다. 내용 기반 검색(Content-based Retrieval)에 관한 대부분의 기존의 질의 방법은 입력 영상에 의한 질의 또는 컬러(color), 형태(shape), 질감(texture)등과 같은 low-level의 특징을 사용한다. 본 논문에서 제안하는 방법은 MPEG 기반의 압축 비디오 스트림으로부터 장면 전환 검출을 수행하여 샷을 검출한다. 이 샷 프레임에서 컬러 객체의 자동 추출을 위하여 similar colorization과 ACE(Adaptive Circular filter and Edge) 알고리즘을 사용한다. 그리고 이렇게 추출된 특징을 해마 신경망을 통하여 학습한 후 멀티미디어 검색 시스템을 구성한다. 제안하는 해마 신경망은 호감도 조정에 의해서 입력되는 영상패턴의 특징들을 흥분학습과 억제학습을 이용하여 불필요한 특징은 억제시키고 중요한 특징은 흥분학습을 통해 장기기억 시켜서 적응성 있는 실시간 검색 시스템을 구현한다.

• 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.

• 한국정보처리학회논문지
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• 제7권2S호
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• pp.678-691
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• 2000

A variety of multimedia applications require multimedia database management systems to manage multimedia data, such as text, image, and video, as well as t support content-based image or video retrieval. In this paper we design and implement a content-based image retrieval system, BADA-IV/I$^2$R(Image Information Retrieval), which is developed based on BADA-IV multimedia database management system. In this system image databases can be efficiently constructed and retrieved with the visual features, such as color, shape, and texture, of image. we extend SQL statements to define image query based on both annotations and visual features of image together. A high-dimensional index structure, called CIR-tree, is also employed in the system to provide an efficient access method to image databases. We show that BADA-IV/I$^2$R provides a flexible way to define query for image retrieval and retrieves image data fast and effectively: the effectiveness and performance of image retrieval are shown by BEP(Bull's Eye Performance) that is used to measure the retrieval effectiveness in MPEG-7 and comparing the performance of CIR-tree with those of X-tree and TV-tree, respectively.